AGV trolley host computer regulation system

Abstract

The application belongs to the technical field of AGV trolley regulation and control, in particular to an AGV trolley host computer regulation and control system, comprising: a data acquisition module, which is used for acquiring the running state data, mechanical response data and environmental physical disturbance data of the AGV trolley formation in real time; the environmental physical disturbance data comprises actual ground skid rate and rudder wheel real-time torque load rate; a global formation rigidity cooperation evaluation module, which is used for constructing a global formation rigidity cooperation model based on the dynamic integral values of the relative geometric distance deviation between vehicles, the formation shear deformation angle and the attitude deviation angle, and acquiring the global formation rigidity cooperation coefficient; the problems of formation shear deformation, non-uniform scaling distortion caused by the independent conversion of the coordinate system by the traditional system relying on its own attitude angle, and systematic formation drift caused by the lack of global maintenance mechanism are solved, and the visual integrity of the performance and the consistency of the cooperative execution are ensured.

Description

Technical Field

[0001] This invention belongs to the field of AGV (Automated Guided Vehicle) control technology, specifically an AGV host computer control system. Background Technology

[0002] AGVs (Automated Guided Vehicles) are an important component of modern automation systems and are widely used in warehousing, manufacturing, and large-scale stage performances. In these applications, the host computer control system is responsible for the coordinated command, path planning, and task assignment of multiple AGVs. Conventional control systems typically provide two modes: program editing and actual operation. This allows directors to design the trajectories and actions of multiple AGVs in a unified virtual coordinate system. At the same time, in order to adapt to complex on-site environments, the host computer will establish corresponding coordinate system mapping and transformation mechanisms to apply the edited trajectories to the actual stage.

[0003] However, existing control systems use different coordinate systems during the program editing and operation phases. During editing, the vehicle's head is assumed to coincide with the coordinate axis (attitude angle 0°). However, during actual operation, each vehicle has different attitude angles. If each vehicle independently transforms its coordinate system based solely on its own attitude angle, the trajectory vector will rotate at different angles. This will disrupt the relative positional relationships defined during the editing phase, causing unexpected formation shearing deformation and non-uniform scaling distortion, which will affect the overall visual integrity of the performance. Furthermore, existing systems lack a global consistency maintenance and dynamic verification mechanism for inter-vehicle geometric constraints, and cannot effectively overcome systemic formation drift caused by physical disturbances such as ground slippage.

[0004] Therefore, the present invention provides an AGV (Automated Guided Vehicle) upper computer control system. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0006] The technical solution adopted by this invention to solve its technical problem is: an AGV (Automated Guided Vehicle) upper computer control system, comprising: The data acquisition module is used to acquire real-time operating status data, mechanical response data, and environmental physical disturbance data of the AGV convoy; the environmental physical disturbance data includes the actual ground slip rate and the real-time torque load rate of the steering wheel. The global formation rigidity cooperative evaluation module is used to construct a global formation rigidity cooperative model and obtain the global formation rigidity cooperative coefficient by using the dynamic integral values ​​of the inter-vehicle relative geometric distance deviation, formation shear deformation angle and attitude deviation angle obtained in real time by the positioning system and attitude sensors. The spatial trajectory fidelity evaluation module is used to construct a spatial trajectory fidelity model and obtain spatial trajectory fidelity coefficients by using the lateral tracking error of the B-spline curve, the out-of-tolerance value of the motion following position, and the absolute zero position offset of the steering wheel obtained by the positioning sensor and the angle sensor. The electromechanical link steady-state evaluation module is used to construct an electromechanical link steady-state model and obtain electromechanical link steady-state coefficients by monitoring and acquiring the transient voltage drop of the servo bus, the multi-axis synchronization time deviation, and the dead zone ionization of the analog input of the joystick through the underlying hardware sensors. The system manifold conformance calculation module is used to obtain the system manifold conformance coefficient by performing exponential dimensionality reduction coupling based on the spatial trajectory fidelity coefficient and the electromechanical link steady-state coefficient, combined with the environmental physical disturbance data. The maximum speed safety margin control module is used to construct a maximum speed optimization model based on the system manifold conformity coefficient, the design maximum speed of the local trajectory segment, and the dynamic safety margin coefficient, output the maximum speed of the target local trajectory segment, and send it to the AGV for execution.

[0007] The beneficial effects of this invention are as follows: 1. The AGV (Automated Guided Vehicle) upper computer control system of the present invention converts the absolute trajectory points of each AGV into polar coordinate descriptions relative to the virtual geometric center, extracts the actual rigid geometric relationship and subtracts it from the design benchmark, effectively eliminating the trajectory vector rotation error caused by the individual posture angle differences of the vehicles. At the same time, it obtains the global formation rigidity coordination coefficient based on the dynamic integral values ​​of the relative geometric distance deviation between vehicles, the formation shear deformation angle and the posture deviation angle. This solves the problems of formation shear deformation, non-uniform scaling distortion caused by the independent transformation of the coordinate system by the posture angle of the traditional system, as well as the systemic formation drift caused by the lack of a global maintenance mechanism. It effectively ensures the visual integrity of the performance and the consistency of the collaborative execution.

[0008] 2. The AGV (Automated Guided Vehicle) upper computer control system of the present invention uses the spatial trajectory fidelity coefficient and the electromechanical link steady-state coefficient as the base, and introduces the actual ground slip rate and the real-time torque load rate of the steering wheel as exponential penalty terms for dimensionality reduction coupling. This mechanism enables the system to sensitively and accurately quantify the nonlinear effects of the external physical environment on trajectory tracking accuracy and underlying electromechanical steady state when facing complex working conditions such as slippery ground or excessive steering load. This overcomes the limitations of traditional solutions that rely on only a single parameter and lack deep coupling of environmental disturbances, and provides the upper computer with a comprehensive evaluation index that can fully characterize the overall operational health of the AGV.

[0009] 3. The AGV (Automated Guided Vehicle) upper computer control system of the present invention exponentially couples the maximum design speed of a local trajectory segment, the system manifold conformity coefficient, and the dynamic safety margin coefficient. When the safety margin approaches 0, the target maximum speed triggers nonlinear exponential collapse decay, rapidly and significantly reducing speed to avoid potential collisions. Subsequently, the upper computer, combined with preset acceleration and deceleration parameters, recalculates the distance and generates continuous and non-abrupt acceleration-uniform speed-deceleration execution commands. This avoids mechanical impact while giving the AGV formation excellent active safety protection capabilities under extreme working conditions. Attached Figure Description

[0010] The invention will now be further described with reference to the accompanying drawings.

[0011] Figure 1 This is a schematic diagram of the overall system architecture and module data flow in this invention; Figure 2 This is a flowchart of the vehicle coordinate transformation and deviation extraction process in this invention; Figure 3 This is a flowchart of the system manifold shape preservation exponential dimensionality reduction coupling in this invention; Figure 4 This is a flowchart of the maximum speed regulation and smooth execution logic in this invention; Figure 5 This is a flowchart of the global formation rigidity coordination coefficient calculation in this invention. Detailed Implementation

[0012] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0013] An AGV (Automated Guided Vehicle) control system according to an embodiment of the present invention includes: The data acquisition module is used to acquire real-time operating status data, mechanical response data, and environmental physical disturbance data of the AGV convoy; the environmental physical disturbance data includes the actual ground slip rate and the real-time torque load rate of the steering wheel; The global formation rigidity cooperative evaluation module is used to construct a global formation rigidity cooperative model and obtain the global formation rigidity cooperative coefficient by using the dynamic integral values ​​of the inter-vehicle relative geometric distance deviation, formation shear deformation angle and attitude deviation angle obtained in real time by the positioning system and attitude sensors. The spatial trajectory fidelity evaluation module is used to construct a spatial trajectory fidelity model and obtain spatial trajectory fidelity coefficients by using the lateral tracking error of the B-spline curve, the out-of-tolerance value of the motion following position, and the absolute zero position offset of the steering wheel obtained by the positioning sensor and the angle sensor. The electromechanical link steady-state evaluation module is used to construct an electromechanical link steady-state model and obtain electromechanical link steady-state coefficients by monitoring and acquiring the transient voltage drop of the servo bus, the multi-axis synchronization time deviation, and the dead zone ionization of the analog input of the joystick through the underlying hardware sensors. The system manifold conformance calculation module is used to obtain the system manifold conformance coefficient by exponentially reducing and coupling the spatial trajectory fidelity coefficient and electromechanical link steady-state coefficient, combined with environmental physical disturbance data. The maximum speed safety margin control module is used to construct a maximum speed optimization model based on the system manifold conformity coefficient, the design maximum speed of the local trajectory segment, and the dynamic safety margin coefficient, output the maximum speed of the target local trajectory segment, and send it to the AGV for execution.

[0014] The data acquisition module is responsible for acquiring the operating status data, mechanical response data, and environmental physical disturbance data of the AGV convoy. It can obtain operating status information such as position, speed, and attitude through sensors installed on the AGV (such as encoders, inertial measurement units, lidar, etc.). Mechanical response data can be obtained by monitoring motor current, voltage, or feedback signals from the steering mechanism. Environmental physical disturbance data, such as the actual ground slip rate, can be estimated by comparing the difference between wheel speed and actual vehicle speed. The real-time torque load rate of the steering wheel can be calculated through the current or torque sensor data of the steering wheel drive motor. In one implementation, the data acquisition module can simply transmit the raw sensor data directly to the host computer for processing.

[0015] The global formation rigidity cooperative evaluation module is used to construct a global formation rigidity cooperative model based on the dynamic integral values ​​of the relative geometric distance deviation between vehicles, the formation shear deformation angle, and the attitude deviation angle, and to obtain the global formation rigidity cooperative coefficient. This can be achieved by deploying a UWB (ultra-wideband) positioning module or a vision recognition system on the AGV, which measures the relative distance and angle between each AGV in real time and compares them with a preset formation benchmark, thereby calculating the distance deviation and shear deformation angle. The dynamic integral value of the attitude deviation angle can be obtained by integrating the output of the AGV's attitude sensor.

[0016] The spatial trajectory fidelity evaluation module is used to construct a spatial trajectory fidelity model based on the lateral tracking error of the B-spline curve, the out-of-tolerance value of the motion following position, and the absolute zero offset of the steering wheel, and to obtain the spatial trajectory fidelity coefficient. For example, when the AGV is executing a B-spline curve trajectory, the real-time position of the AGV can be obtained through the on-board GPS or visual positioning system and compared with the B-spline curve to calculate the lateral tracking error. The out-of-tolerance value of the motion following position can be obtained by comparing the position difference between the actual position of the AGV and the target trajectory point. The absolute zero offset of the steering wheel can be obtained by zero-position calibration when the AGV starts and by continuously monitoring the encoder feedback value of the steering wheel. In one implementation, this module can only focus on whether the AGV is within the preset trajectory zone without performing fine-grained modeling of the specific error.

[0017] The electromechanical link steady-state evaluation module is used to construct an electromechanical link steady-state model and obtain electromechanical link steady-state coefficients based on the transient voltage drop of the servo bus, the multi-axis synchronization time deviation, and the dead zone detachment of the joystick analog input. For example, the transient voltage drop of the servo bus can be monitored in real time by installing a voltage sensor on the servo driver bus; the multi-axis synchronization time deviation can be calculated by comparing the motion command issuance time and the actual response time of each drive axis of the AGV; and the dead zone detachment of the joystick analog input can be obtained by sampling and analyzing the fluctuation of the joystick analog input signal in the no-operation state. In one implementation, the module can determine the steady-state condition of the electromechanical link simply by monitoring whether the servo bus voltage is lower than a certain fixed alarm value.

[0018] The system manifold conformance calculation module is used to obtain the system manifold conformance coefficient by exponentially reducing and coupling the spatial trajectory fidelity coefficient and electromechanical link steady-state coefficient with environmental physical disturbance data. For example, the module can take the obtained spatial trajectory fidelity coefficient and electromechanical link steady-state coefficient as inputs, and combine them with environmental physical disturbance data such as actual ground slip rate and real-time torque load rate of steering wheel, and calculate a comprehensive system manifold conformance coefficient through a preset mathematical function.

[0019] The maximum speed safety margin control module is used to construct a maximum speed optimization model based on the system manifold conformity coefficient, the design maximum speed of the local trajectory segment, and the dynamic safety margin coefficient. It outputs the maximum speed of the target local trajectory segment and sends it to the AGV for execution. For example, this module can receive the system manifold conformity coefficient and, in combination with the preset design maximum speed of the current trajectory segment and the dynamic safety margin coefficient obtained by anti-collision sensors, calculate the actual maximum speed at which the AGV can safely run on the trajectory segment through an optimization algorithm. The calculated target maximum speed is then sent to the AGV to guide it in adjusting its running speed.

[0020] The system manifold conformity calculation module exponentially couples the above evaluation results with environmental physical disturbance data, providing a core indicator that comprehensively reflects the overall conformity-keeping capability of the system. This differs from existing technologies that rely on a single or limited parameter for judgment. As a result, the maximum speed safety margin control module can dynamically optimize the design maximum speed of local trajectory segments based on this comprehensive indicator, rather than using fixed speed limits or simple linear adjustments. When the system manifold conformity coefficient decreases due to ground slippage, the system can actively reduce the target maximum speed of the AGV, thereby avoiding formation instability or trajectory deviation caused by high-speed operation. This dynamic and adaptive speed control mechanism enables the AGV formation to continuously maintain its preset formation and trajectory accuracy in complex and ever-changing environments, effectively overcoming the formation shearing deformation, non-uniform scaling distortion, and systemic formation drift problems that traditional existing systems cannot solve, ensuring the consistency of multi-vehicle collaborative trajectory execution.

[0021] In the global formation rigidity coordination evaluation module, the methods for obtaining the global formation rigidity coordination coefficient include: A1: After obtaining the instantaneous attitude deviation by comparing the real-time attitude angle of the AGV with the desired attitude angle, the dynamic integral value of the attitude deviation angle is obtained by performing an integral calculation within a preset time window. A2: Calculate the ratio of the dynamic integral values ​​of the relative geometric distance deviation between vehicles, the formation shear deformation angle, and the attitude deviation angle to their respective reference thresholds for dimensionless processing. A3: The reference thresholds include the relative distance allowable reference threshold, the shear angle allowable reference threshold, and the attitude angle integral reference threshold; A4: Square each ratio after dimensionless processing, multiply each by the corresponding normalized weighting coefficient, and then sum them; the sum of the normalized weighting coefficients is limited to one. A5: Perform a square root operation on the summation result to obtain the comprehensive error norm; A6: The negative value of the comprehensive error norm is used as the exponent of the natural exponential function to calculate the global formation rigidity coordination coefficient that decays continuously in the interval (0,1].

[0022] In the global formation rigidity coordination evaluation module, the global formation rigidity coordination coefficient is obtained. The model formula is: In the formula, The relative geometric distance deviation between vehicles (unit: ), The relative distance allowable reference threshold (unit: ); Formation shear deformation angle (unit: ), Shear angle allowable reference threshold (unit: ); The dynamic integral value of the attitude deviation angle (unit: ), Attitude angle integral reference threshold (unit: ); , , All are normalized weight coefficients (dimensionless) and satisfy the following conditions: .

[0023] This model defines a method for quantifying the rigidity and coordination of AGV formations. It integrates multiple formation deviation indices into a single coefficient using an exponential decay function. The magnitude of this coefficient directly reflects the degree of deviation between the formation and the preset rigid geometric constraints. This model can be implemented in the central processing unit of a host computer control system using software algorithms and calculated in real time using a floating-point unit.

[0024] Among them, the relative geometric distance deviation between vehicles The relative geometric distance between any two AGVs in an AGV formation is the difference between the actual relative geometric distance and the designed or expected relative geometric distance. It is a key indicator for measuring the overall scaling or expansion of the formation. This deviation can be obtained by acquiring the real-time position information of each AGV through a data acquisition module (e.g., through GPS, UWB, LiDAR, SLAM, and other positioning systems), then calculating the Euclidean distance between any two AGVs and comparing it with the preset ideal distance; alternatively, it can be obtained by using a vision system, such as a camera installed on the AGV, to identify specific marker points of adjacent vehicles, calculate the relative distance through image processing, and compare it with a reference value.

[0025] Relative distance allowable reference threshold The maximum acceptable deviation of relative geometric distance between vehicles is defined. When the actual deviation exceeds this threshold, the formation rigidity is considered to be significantly affected. This threshold can be preset through experimental testing or simulation analysis based on the physical size, motion characteristics, and formation accuracy requirements of the AGV vehicle in the application scenario.

[0026] Formation shear deformation angle In AGV formations, changes in the posture or relative position of each vehicle cause the overall formation to undergo non-uniform deformation, similar to that under shear force. This manifests as a deviation in the angular relationships of the formation. These angles can be obtained by acquiring the real-time posture angles of each AGV vehicle through a data acquisition module (e.g., via an IMU or visual inertial navigation system). Combined with the position information of each vehicle, a virtual geometric structure (such as a triangle or quadrilateral) in the formation is constructed. Then, the deviations between the internal angles of these structures and the ideal formation angles are calculated.

[0027] Shear angle allowable reference threshold The maximum acceptable shear deformation angle of the formation is defined. If this threshold is exceeded, the formation shear deformation is considered to be too large, affecting the stability of the formation. This threshold can be determined by expert experience or optimization algorithm based on the kinematic and dynamic characteristics of the AGV, the visual requirements for maintaining the formation, and the accuracy requirements of the task.

[0028] Dynamic integral value of attitude deviation angle The dynamic integral refers to the cumulative deviation between the AGV's own attitude angle and the desired attitude angle over a period of time. The dynamic integral can reflect the persistence and cumulative effect of the attitude deviation, rather than just the instantaneous deviation. This integral value can be obtained by acquiring the AGV's real-time attitude angle (such as heading angle) through the data acquisition module, comparing it with the desired attitude angle issued by the host computer to obtain the instantaneous attitude deviation, and then performing an integral calculation on the deviation within a certain time window.

[0029] Attitude angle integral reference threshold The maximum acceptable limit for the dynamic integral value of the attitude deviation angle is defined. When the cumulative deviation exceeds this threshold, it indicates that there is a problem with the attitude maintenance capability of the AGV. This threshold can be determined through system calibration and performance testing based on the control accuracy of the AGV, the sensor noise level, and the requirements of the formation for attitude synchronization. Alternatively, different thresholds can be set according to the attitude control difficulty of the AGV under different motion states (such as straight driving and turning).

[0030] Normalized weighting coefficients , , The dynamic integral values ​​of the relative geometric distance deviation between vehicles, the formation shear deformation angle, and the attitude deviation angle are used to adjust the relative importance of these factors in the calculation of the global formation rigidity coordination coefficient. They satisfy the normalization condition that the sum is 1, ensuring that the contribution of each factor can be flexibly configured. These weight coefficients can be manually set according to the specific application scenario and the emphasis on formation stability.

[0031] The global formation rigidity coordination evaluation module quantifies the multi-dimensional formation deviations generated during AGV vehicle formation operation into a single global formation rigidity coordination coefficient by constructing an exponential decay model. The core of this model lies in comprehensively considering the relative geometric distance deviation between vehicles. Formation shear deformation angle and the dynamic integral value of the attitude deviation angle These three key indicators.

[0032] The data acquisition module acquires real-time operational status data of the AGV convoy, including the position and attitude information of each AGV. After receiving this data, the global formation rigidity collaborative evaluation module first calculates the relative geometric distance deviation between each AGV. That is, the difference between the actual distance and the expected distance; next, the formation shear deformation angle is calculated. This reflects the degree of distortion in the geometric shape of the formation; simultaneously, the attitude deviation of each AGV is dynamically integrated to obtain the dynamic integral value of the attitude deviation angle. To capture the cumulative effect of attitude deviation, and to eliminate the influence of different physical dimensions and unify the evaluation criteria, the above three deviation values ​​are respectively compared with their corresponding allowable reference thresholds (relative distance allowable reference thresholds). Shear angle allowable reference threshold Attitude angle integral reference threshold The deviation terms are then normalized, and subsequently, these normalized deviation terms are normalized using preset normalization weighting coefficients. , , Perform a weighted sum of squares calculation and take the square root to form a comprehensive deviation index.

[0033] Finally, this comprehensive deviation index is substituted into the exponential decay function to generate the global formation rigidity synergy coefficient. This exponential decay characteristic means that when any deviation term increases significantly, the coordination coefficient drops rapidly, thus sensitively reflecting the deterioration of formation rigidity. In this way, the scheme can comprehensively and objectively assess the distortion of AGV formation in spatial distribution and attitude maintenance, simplifying the complex problem of formation stability into an intuitive quantitative indicator. The value range of this coefficient is typically within... The coefficient is between 1 and 0, where 1 indicates that the formation fully conforms to the rigid constraints, while a value close to 0 indicates that the formation deviates significantly. This quantitative assessment provides the host computer control system with accurate formation status perception capabilities, enabling the system to adjust the speed of the AGV based on this coefficient to actively maintain formation stability and overcome the shortcomings of traditional systems in formation maintenance.

[0034] This application overcomes the limitations of traditional systems that lack quantitative evaluation standards, enabling the host computer to perceive the formation distortion of AGV formations in real time and accurately. By converting multi-dimensional formation deviations into a single global formation rigidity coordination coefficient, the judgment and decision-making process of formation status is greatly simplified. This coefficient can intuitively reflect the degree of formation rigidity maintenance, providing a reliable decision basis for the host computer to adjust the speed of each AGV to maintain formation stability. Especially when AGV formations are performing complex trajectory movements or facing external disturbances, this coefficient can sensitively capture changes in formation, thereby triggering the control mechanism in a timely manner, effectively avoiding formation shearing deformation and non-uniform scaling distortion, significantly improving the stability and coordination accuracy of AGV formation operation, and ensuring the quality of task execution and visual effects.

[0035] In the spatial trajectory fidelity evaluation module, the methods for obtaining the spatial trajectory fidelity coefficient include: B1: The lateral tracking error of the B-spline curve is calculated by obtaining the global coordinates of the vehicle through the positioning sensor and combining them with the preset mathematical model of the B-spline curve. The position deviation during motion tracking is obtained by comparing the theoretical position calculated from odometry integration with the actual positioning position. The absolute zero offset of the steering wheel is obtained by measuring the actual angle using a steering wheel encoder or angle sensor and comparing it with the theoretical zero position. B2: Calculate the ratio of the lateral tracking error of the B-spline curve, the out-of-tolerance value of the motion following position, and the absolute zero position offset of the steering wheel to their respective tolerance thresholds, and perform dimensionless processing. The tolerance thresholds include the lateral error tolerance, the out-of-tolerance limit threshold, and the zero-point deviation tolerance threshold. B3: Calculate the nonlinear even powers of each ratio after dimensionless processing to obtain the exponential penalty value of each parameter; B4: Summing the exponential penalty values ​​of each parameter to obtain the polynomial error accumulation value, then adding one to the polynomial error accumulation value and taking the reciprocal to calculate the spatial trajectory fidelity coefficient.

[0036] In the spatial trajectory fidelity evaluation module, the spatial trajectory fidelity coefficient is obtained. The (dimensionless) model formula is: In the formula, The lateral tracking error of the B-spline curve (unit: ), Lateral error tolerance (unit: ); The position deviation of motion tracking (unit: ), Threshold for out-of-tolerance limits (unit: ); The absolute zero offset of the steering wheel (unit: ), Zero-position deviation tolerance threshold (unit: ); , , All are non-linear penalties of even powers (dimensionless).

[0037] The model formula aims to quantify the degree to which the AGV follows the preset spatial trajectory by comprehensively considering various trajectory deviation factors. Its core idea is to normalize each error term, then perform weighted accumulation by nonlinear penalty even powers, and map it to a coefficient between 0 and 1 in reciprocal form, where 1 represents complete fidelity and close to 0 represents serious deviation.

[0038] Among them, the lateral tracking error of the B-spline curve This refers to the vertical distance from the current actual position of the AGV to the nearest point of its planned B-spline curve. It reflects the degree to which the vehicle deviates from the preset path in the lateral direction. This error can be obtained by using positioning sensors such as GNSS (Global Navigation Satellite System) or LiDAR on the AGV to obtain the vehicle's global coordinates in real time and then calculating them in combination with the preset B-spline curve mathematical model.

[0039] Lateral error tolerance This represents the maximum threshold for the lateral tracking error of the B-spline curve allowed by the system. When the actual lateral tracking error exceeds this threshold, the system considers the AGV trajectory to be seriously deviated. This tolerance can be preset according to factors such as the application scenario, path width, and safety requirements of the AGV; it can also be adaptively adjusted according to dynamic parameters such as the speed and turning radius of the AGV.

[0040] Motion tracking position deviation This refers to the distance deviation between the current actual position of the AGV and the target position that should be reached at the corresponding time on the planned trajectory. It reflects the degree to which the AGV is ahead or behind the planned progress during its movement. This error can be obtained by comparing the theoretical position calculated by integrating the AGV's internal odometer and the planned speed with the actual position provided by the GNSS or SLAM (Simultaneous Localization and Mapping) system.

[0041] Out-of-tolerance threshold This represents the maximum threshold for the allowable deviation in the AGV's tracking position. When the actual tracking position deviation exceeds this threshold, the system considers the AGV's tracking performance to be poor. This threshold can be set according to the AGV's task accuracy requirements, formation coordination needs, etc.; it can also be dynamically adjusted based on environmental factors such as the AGV's load and the ground friction coefficient.

[0042] Steering wheel absolute zero offset This refers to the actual angular deviation of the steering wheel of the AGV when it should theoretically be at the zero position for straight-line travel. It reflects the mechanical precision of the steering mechanism, sensor zero-point drift, or control system error. This offset can be obtained by directly measuring the actual angle of the steering wheel through a steering wheel encoder or angle sensor and comparing it with the theoretical zero position.

[0043] Zero-position deviation tolerance threshold This represents the maximum threshold for the absolute zero offset of the steering wheel that the system allows. When the actual absolute zero offset of the steering wheel exceeds this threshold, the system considers there to be a problem with the steering control. This threshold can be set according to the mechanical precision of the steering mechanism, the response speed of the control system, and the driving stability requirements of the AGV.

[0044] Nonlinear penalty even power , , This is used to nonlinearly amplify and penalize various errors. Since it is an even power, it ensures that the penalty term is always positive. Moreover, as the error increases, the penalty effect grows exponentially, so that even small errors can have a significant impact on the fidelity coefficient when they approach the tolerance threshold. These powers can be empirically set according to the sensitivity of each error to the trajectory fidelity; or they can be optimized and adjusted by machine learning algorithms based on historical running data and expert experience.

[0045] The solution proposed in this application achieves a quantitative evaluation of the trajectory tracking quality of AGV vehicles by constructing a spatial trajectory fidelity model. This model uses a denominator summation method to account for the lateral tracking error of the B-spline curve. Motion following position deviation and the absolute zero offset of the steering wheel As core input variables, their respective horizontal error tolerances are used. Out-of-tolerance threshold and zero-position deviation tolerance threshold Normalization is performed, which allows errors of different dimensions to be compared and accumulated on a unified scale. The normalized errors are then penalized by an even power of a nonlinear penalty. , , Weighting is applied so that when any deviation approaches or exceeds its tolerance threshold, the corresponding penalty term increases rapidly, thereby affecting the spatial trajectory fidelity coefficient. The error decreases non-linearly. Finally, by dividing 1 by 1 and adding the sum of all penalty terms, the overall error is mapped to a coefficient between 0 and 1, where 1 represents perfect fidelity and the smaller the value, the more severe the trajectory deviation.

[0046] The fidelity coefficient of the spatial trajectory The acquisition of this value provides a key input for the system manifold conformity calculation module, which uses this spatial trajectory fidelity coefficient. Based on the steady-state coefficient of the electromechanical link, and combined with environmental physical disturbance data for exponential dimensionality reduction coupling, the system manifold conformity coefficient is obtained. This synergistic effect enables the host computer not only to evaluate the degree to which the AGV follows the planned trajectory, but also to comprehensively consider this degree of compliance with the stability of the electromechanical system and environmental disturbance factors. This allows for a more comprehensive and accurate assessment of the overall operating status of the AGV, providing a reliable basis for subsequent maximum speed safety margin control. It effectively overcomes the limitations of traditional single-index evaluation, providing a sensitive and reliable trajectory quality evaluation index, ensuring that the system can promptly detect trajectory deviation risks and perform corresponding speed optimizations, thereby improving the operational safety and stability of the AGV in complex dynamic environments.

[0047] By nonlinearly coupling three key errors—lateral tracking error of B-spline curve, out-of-tolerance value of motion following position, and absolute zero-position offset of steering wheels—and mapping them to a single spatial trajectory fidelity coefficient, the system can more comprehensively and sensitively perceive the degree to which the AGV follows the preset spatial trajectory. This comprehensive quantification mechanism effectively overcomes the limitations of traditional single-index evaluation and avoids potential safety hazards caused by the neglect of a certain error. When any error approaches or exceeds the tolerance threshold, the spatial trajectory fidelity coefficient will show a significant nonlinear decrease, thus providing the host computer with a sensitive and reliable trajectory quality evaluation index, ensuring that the system can promptly detect trajectory deviation risks.

[0048] Furthermore, the spatial trajectory fidelity coefficient, as a key input to the system manifold conformity calculation module, works together with the electromechanical link steady-state coefficient and environmental physical disturbance data to enable the host computer to more accurately evaluate the overall operating status of the AGV, thereby significantly improving the operational safety and stability of the AGV in complex dynamic environments.

[0049] In the electromechanical link steady-state evaluation module, the steady-state coefficients of the electromechanical link are obtained. The model formula is: In the formula, Transient voltage drop of the servo bus (unit: ), Undervoltage alarm threshold (unit: ); Multi-axis synchronization time deviation (unit: ), Upper limit of synchronization time tolerance (unit: ); Input dead zone free zone degree for analog input of joystick (unit: ), Noise floor filtering threshold (unit: ); , , All are sensitivity gain constants (dimensionless).

[0050] Among them, the transient voltage drop of the servo bus is calculated by monitoring the voltage value on the DC bus of the servo driver; the multi-axis synchronization time deviation is obtained by comparing the sending and execution time of motion commands recorded by the timestamp module; and the dead zone ionization is obtained by continuously collecting data and calculating the fluctuation range by the analog-to-digital converter when the joystick is stationary.

[0051] Among them, the transient voltage drop of the servo bus This refers to a rapid and unexpected drop in the power bus voltage within a short period of time in an AGV servo drive system. This can be addressed by connecting a high-precision voltage sensor in parallel with the DC bus of the servo drive, monitoring the voltage value in real time, comparing it with a preset steady-state voltage, and calculating the transient voltage drop.

[0052] Undervoltage alarm threshold This refers to the minimum voltage limit allowed for the normal operation of the servo system. Below this value, the system performance may degrade or the system may shut down. This threshold can be set according to the technical specifications or system design requirements provided by the servo drive manufacturer; alternatively, it can be dynamically adjusted through system self-learning or expert experience, combined with the actual voltage fluctuations of the AGV under different loads and operating modes.

[0053] Multi-axis synchronization time deviation This refers to the difference between the actual start or end time of motion between each axis and the ideal synchronization time in the multi-axis motion control system of an AGV. It can be achieved by deploying high-precision timestamp modules on each axis controller to record the sending and execution time of key motion commands, and then comparing and calculating the difference through a host computer.

[0054] Synchronization time tolerance limit This refers to the maximum allowable time deviation between axes in multi-axis synchronous motion. Exceeding this limit may affect motion accuracy and formation stability. This upper limit can be set by system engineers based on their experience and the requirements for synchronization accuracy in the application scenario of the AGV. Alternatively, it can be determined through experimental testing under different operating speeds and load conditions to maintain acceptable motion quality.

[0055] Joystick Analog Input Dead Zone Freeness In the AGV control system, the fluctuation range of the output signal of analog input devices such as joysticks when they are not operated or are in a dead zone can be calculated by connecting a high-resolution ADC (analog-to-digital converter) to the analog input channel, continuously collecting data when the joystick is stationary, and calculating the peak-to-peak value of the fluctuation range to ensure the uniqueness of the measurement method.

[0056] Noise floor filtering threshold This refers to the threshold value used to distinguish effective control signals from background noise. Signal fluctuations below this threshold are considered noise. This threshold can be set according to the technical parameters of the joystick sensor, the accuracy of the ADC, and the system's tolerance to noise. Alternatively, it can be set by collecting analog input data from the joystick over a long period of time while the AGV is stationary, statistically analyzing its noise distribution characteristics, and then setting a suitable threshold.

[0057] Sensitivity gain constant , , The parameters used to adjust the influence of various evaluation factors on the steady-state coefficient of the electromechanical link reflect the system's sensitivity to different disturbances. These constants can be empirically adjusted based on the actual response of the AGV to voltage, synchronization, and noise under different operating conditions through system debugging and experimental verification; or they can be optimized in a simulation environment through optimization algorithms to achieve the best steady-state evaluation effect.

[0058] By reducing the transient voltage of the servo bus Multi-axis synchronization time deviation and the dead zone and free degree of analog input of the joystick As a core evaluation indicator, for each indicator, it is compared with its respective allowable benchmark threshold (undervoltage alarm threshold). Synchronization time tolerance limit Noise floor filtering threshold Perform ratio calculations and combine them with the sensitivity gain constant. , , By performing a nonlinear mapping using the hyperbolic tangent function, a steady-state factor between 0 and 1 is generated.

[0059] When transient voltage drop, synchronization deviation, or dead zone ionization are small, the corresponding steady-state factor approaches 1, indicating that the electromechanical link is in a good steady state. Conversely, when these deviations increase, the steady-state factor will decrease rapidly, reflecting a decline in the health of the electromechanical link. Finally, by multiplying and coupling these three independent steady-state factors, the steady-state coefficient of the electromechanical link is obtained. This product coupling method ensures that if any key electromechanical component becomes significantly unstable, the overall electromechanical link steady-state coefficient will decrease significantly, thus comprehensively reflecting the overall steady-state level of the electromechanical link.

[0060] The steady-state coefficient of the electromechanical link As an important input in the AGV's host computer control system, it can be further utilized by the system's manifold conformity calculation module. Combined with the spatial trajectory fidelity coefficient and considering the exponential dimensionality reduction coupling of environmental physical disturbance data, it ultimately affects the maximum speed safety margin control module's output of the maximum speed of the target local trajectory segment. This mechanism enables the host computer control system to dynamically adjust its operating strategy based on the actual electromechanical health status of the AGV's underlying structure, thereby maintaining high-precision motion control under complex working conditions. This effectively overcomes the problem of decreased control performance caused by the lack of quantitative evaluation of underlying electromechanical parameters in traditional systems.

[0061] In the system manifold conformity calculation module, the system manifold conformity coefficients are obtained. The model formula is: In the formula, is the spatial trajectory fidelity coefficient (dimensionless). , is the steady-state coefficient of the electromechanical link (dimensionless). The actual ground slip rate (dimensionless). Real-time torque load rate of the steering wheel (dimensionless). and All are physical disturbance intensity penalty constants (dimensionless), and and The range of values ​​is all within Between (dimensionless).

[0062] The actual ground slip rate is calculated by comparing the rotational speed of the AGV's drive wheels with the actual vehicle speed; the real-time torque load rate of the steering wheel is obtained by monitoring the motor's output torque using a current sensor or torque sensor on the motor and comparing it with the maximum rated torque.

[0063] The manifold conformity calculation module of this system is a functional unit in the AGV upper computer control system. Its main function is to comprehensively evaluate the overall operating status of the AGV in complex environments. It can be an independent software process, a hardware acceleration unit, or an algorithm library integrated in the main controller. It is responsible for receiving evaluation coefficients and environmental data from other modules and performing specific mathematical operations to output a comprehensive index. This module is implemented through a C++ or Python program running on the upper computer main control CPU.

[0064] System manifold conformity coefficient The output of this module represents the AGV's ability to maintain its preset trajectory and the stability of its electromechanical system under the current operating state. The value of this coefficient is usually between 0 and 1. The closer the value is to 1, the better the conformity of the system and the more stable and expected the operating state. Conversely, the smaller the value, the greater the impact of disturbances on the system and the lower the conformity.

[0065] Spatial trajectory fidelity coefficient Generated by the spatial trajectory fidelity evaluation module, this coefficient quantifies the degree of fit between the actual running trajectory and the designed trajectory of the AGV. In the system manifold conformity calculation module, this coefficient serves as one of the fundamental inputs for evaluating the overall conformity of the system. (Electromechanical link steady-state coefficient) Generated by the electromechanical link steady-state evaluation module, this coefficient is used to evaluate the operational stability of the AGV's electromechanical system. In the system manifold conformity calculation module, this coefficient serves as another basic input for evaluating the overall conformity of the system.

[0066] Actual ground slip rate It is a type of environmental physical disturbance data used to quantify the relative slippage between the drive wheels of the AGV and the ground. It can be calculated by comparing the rotational speed of the AGV drive wheels with the actual vehicle speed (e.g., obtained through an inertial measurement unit (IMU) or visual odometry (VIO)).

[0067] Steering wheel real-time torque load rate It is a type of environmental physical disturbance data used to quantify the ratio of the real-time torque experienced by the steering wheel of an AGV during steering to its maximum design torque. It can be obtained by monitoring the motor output torque in real time through a current sensor or torque sensor installed on the steering wheel motor and comparing it with the maximum rated torque of the steering wheel.

[0068] Physical disturbance intensity penalty constant and Used to adjust the actual ground slip rate and real-time torque load rate of steering wheel For spatial trajectory fidelity coefficient and electromechanical link steady-state coefficient The degree of influence refers to the parameters calibrated and optimized during system design based on the physical characteristics of the AGV, application scenarios, and sensitivity to different disturbances. Exponential dimensionality reduction coupling is a mathematical processing method that uses the spatial trajectory fidelity coefficient... and electromechanical link steady-state coefficient Using the base as the exponent and the expression containing environmental physical disturbance data as the exponent for product operation, as the environmental disturbance increases, the exponent term increases, thus causing the power of the base to increase, resulting in the final system manifold conformity coefficient. It exhibits a non-linear, exponential decline.

[0069] Spatial trajectory fidelity coefficient and electromechanical link steady-state coefficient With real-time acquired environmental physical disturbance data (i.e., actual ground slip rate) and real-time torque load rate of steering wheel This module performs deep fusion, but instead of simply linearly superimposing these factors, it employs an exponential dimensionality reduction coupling strategy, using the spatial trajectory fidelity coefficient... As the base, its exponent is designed to be This means the actual ground slip rate The increase of this will nonlinearly amplify the penalty effect on the trajectory fidelity coefficient; similarly, the electromechanical link steady-state coefficient... As another base, its exponent is This results in the real-time torque load rate of the steering wheel. Changes in these factors can exponentially affect the steady-state assessment of electromechanical systems. Finally, these two environmentally perturbation-weighted terms are multiplied to generate a single, comprehensive system manifold conformity coefficient. This mechanism can map the originally independent trajectory tracking performance and electromechanical system stability onto a unified indicator that comprehensively reflects the overall operational health of the AGV through the nonlinear effects of environmental disturbances. When the AGV operates under complex conditions, such as slippery ground leading to increased slippage rate, or excessive steering load leading to increased torque load rate, this exponential coupling mechanism will affect the system's manifold conformity coefficient. The rapid and significant decrease in speed allows for accurate capture of the negative impact of the physical environment on the AGV's performance, providing a more precise basis for decision-making in the subsequent maximum speed safety margin control module. In this way, this application effectively solves the problem of lacking deep coupling of environmental physical disturbances in traditional solutions, and achieves accurate characterization of the system's manifold conformity.

[0070] By using the spatial trajectory fidelity coefficient and the electromechanical link steady-state coefficient as bases, and introducing the actual ground slippage rate and the real-time torque load rate of the steering wheel for exponential weighting, dynamic correction and in-depth evaluation of the AGV's operating state are achieved. This enables the system to more sensitively and accurately quantify the nonlinear influence of the physical environment on trajectory fidelity and electromechanical steady-state when facing complex conditions such as ground slippage and excessive steering wheel load. Therefore, the obtained system manifold conformity coefficient... It can more accurately characterize the overall operational health of AGVs, providing a more reliable basis for subsequent maximum speed safety margin adjustment, thereby significantly improving the robustness and consistency of AGV formations in complex physical environments.

[0071] In the maximum speed safety margin control module, the methods for outputting the maximum speed of the target local trajectory segment include: C1: Based on the safety redundancy status reflected by the dynamic safety margin coefficient, reverse risk correlation is performed, and nonlinear sensitivity weighting and exponential mapping are performed in combination with the cliff braking slope factor to obtain the dynamic safety power exponent used to quantitatively characterize the deterioration trend of space safety risks. C2: Based on the dynamic safety power exponent, the nonlinear power function decay constraint is applied to the system manifold conformity coefficient to obtain the nonlinear decay factor of conformity, which is used to comprehensively characterize the coupling characteristics of the system's steady-state operation and external risks. C3: Utilize the shape-preserving nonlinear decay factor to dynamically and adaptively limit and control the maximum speed of the local trajectory segment, thereby obtaining and outputting the maximum speed of the target local trajectory segment.

[0072] The maximum speed safety margin control module outputs the maximum speed of the target's local trajectory segment. (unit: The model formula is: In the formula, The design maximum speed for a local trajectory segment (unit: ); is the system manifold conformity coefficient (dimensionless). The dynamic safety margin coefficient (dimensionless) has a range of values ​​of [value range missing]. ; It is the cliff-like braking slope factor (dimensionless).

[0073] The maximum speed safety margin control module is a core functional unit in the system. Its main responsibility is to intelligently adjust the maximum operating speed of the AGV based on the current operating status of the AGV, the environmental safety conditions, and the preset trajectory parameters. This module can be an independent software service running on the host computer's main control unit, or it can be a specific processing node in a distributed computing architecture. Its implementation methods can include, but are not limited to, using a rule-based expert system to adjust the speed according to preset logic and thresholds.

[0074] System manifold conformity coefficient It is a comprehensive indicator that measures the AGV's ability to maintain formation, track tracking accuracy, and the steady-state performance of its electromechanical system. The higher the value, the more stable the system's operation and the more it meets expectations. The maximum design speed of local trajectory segments is also a key indicator. It refers to Under ideal conditions, the maximum permissible speed, which is pre-planned or set for a specific trajectory segment, is usually determined by path planning algorithms or human experience.

[0075] Dynamic safety margin coefficient This is an indicator that reflects the current safety redundancy status of the AGV in real time. For example, it can be calculated based on factors such as the ratio of the remaining collision avoidance distance fed back by the collision avoidance sensor to the preset parking limit, and the predicted time for the steering axis to reach the hardware limit blind spot. The maximum speed optimization model is the core algorithm of this module. It takes the above coefficients as input and calculates the maximum speed of the target local trajectory segment that the AGV should execute under the current environment through specific mathematical relationships (such as the exponential decay model given in this application). .

[0076] Output the maximum velocity of the target's local trajectory segment. This is the maximum speed that the AGV is actually allowed to run on the current local trajectory segment, obtained after calculation by the optimized model. Sending this speed to the AGV for execution means that the host computer will send the calculated speed... The data is sent to the onboard controller of the AGV via a communication interface (such as Ethernet, WLAN, etc.), and then further analyzed by the onboard controller and used in its motion control algorithm to limit the actual running speed of the AGV.

[0077] Cliff-like braking slope factor It is an adjustment parameter used to control the dynamic safety margin coefficient. When decreasing, the target's maximum speed The degree of decay is indicated by the value; the larger the value, the faster the decay.

[0078] The maximum speed safety margin control module receives the AGV convoy's operational status data, mechanical response data, and environmental physical disturbance data from the data acquisition module. This data is then combined with the system manifold conformity coefficients output by the global formation rigidity collaborative evaluation module, the spatial trajectory fidelity evaluation module, and the electromechanical link steady-state evaluation module. .

[0079] Based on this, the module will design the maximum speed of the local trajectory segment. With system manifold conformity coefficient Perform exponential coupling, utilizing conformality coefficients This scheme reflects the system's current steady-state operation and trajectory fidelity, ensuring that it can proactively reduce speed when the system is in poor condition, thereby guaranteeing overall operational stability. Furthermore, the scheme introduces a dynamic safety margin coefficient. As an adjustment factor for the exponential term, it can reflect the safety redundancy status of the AGV in the physical space in real time. When the dynamic safety margin coefficient... When the dynamic safety margin coefficient When changes occur, the slope factor is used for cliff-like braking. By applying a nonlinear mapping to the speed decay curve, the target speed can be dynamically adjusted according to the level of safety risk. The special feature of this design is that, by utilizing the sensitivity of the exponential function, the target speed will produce a nonlinear and rapid response when the safety margin decreases, thereby minimizing potential collision risks or mechanical limit conflicts while ensuring operational efficiency.

[0080] In this way, the system of this application can comprehensively consider the AGV's own operating status, formation maintenance capability, trajectory tracking accuracy, electromechanical system steady state, and the safety margin of the external environment, so as to achieve refined and adaptive control of the AGV's operating speed and effectively avoid the safety hazards that may occur in traditional systems in complex dynamic environments.

[0081] By introducing a dynamic safety margin coefficient And compare it with the system manifold conformity coefficient. The design maximum speed of local trajectory segments By employing exponential coupling, the system can not only adjust its speed based on the AGV's own operating status and formation maintenance capabilities, but also respond in real time to safety risks in the external environment, such as potential collision risks or mechanical limit conflicts. When the safety margin decreases, the target speed will decay rapidly in a non-linear exponential manner. This ensures the AGV's operating efficiency while minimizing potential risks, significantly improving the safety and reliability of AGV formations in complex dynamic environments.

[0082] The method for obtaining the dynamic safety margin coefficient is as follows: D1: Obtain the ratio of the remaining anti-collision redundancy distance to the preset parking limit fed back by the AGV anti-collision sensor and the predicted time for the steering shaft to reach the hardware limit dead angle, and perform normalization processing by joint calculation. D2: When the dynamic safety margin coefficient approaches 0, the nonlinear decay factor of conformity is triggered, driving the maximum velocity of the target's local trajectory segment to decay nonlinearly and exponentially.

[0083] Among them, the dynamic safety margin coefficient A comprehensive safety assessment index is used to quantify the safety margin of an AGV in its current operating state. This coefficient can be a dimensionless value, typically ranging from 0 to 1, where 1 represents complete safety or maximum margin, and 0 represents extreme danger or a critical state. This coefficient can serve as a key input parameter in the maximum speed optimization model to dynamically adjust the AGV's operating speed. The ratio of the remaining anti-collision redundancy distance fed back by the AGV's anti-collision sensors to the preset parking clearance refers to the ratio calculated by the anti-collision sensors (such as lidar, ultrasonic sensors, and vision sensors) on the AGV to the distance required for the AGV to safely stop at the current speed (i.e., the preset parking clearance). The ratio can intuitively reflect the collision risk of the AGV in the current environment. For example, when the ratio is close to 1, it means that there is enough parking distance; when the ratio is close to 0, it means that the parking distance is insufficient and there is a risk of collision. The prediction time for the steering shaft to reach the hardware limit dead angle refers to the time required for the steering shaft to reach its mechanical limit position (i.e., dead angle) from the current position based on the current motion state of the AGV (such as speed and steering angular velocity) and the physical limitations of the steering mechanism (such as maximum steering angle and steering speed). This prediction time reflects the AGV's response capability to perform obstacle avoidance or steering operations in emergency situations. The shorter the prediction time, the smaller the margin of the AGV in steering operations and the higher the potential risk. The prediction time can be calculated in real time by the motion controller inside the AGV or the host computer system.

[0084] Joint calculation and normalization refers to the process of combining two independent risk assessment indicators—the proportion of the remaining collision avoidance redundancy distance to the preset parking clearance and the predicted time for the steering axis to reach the hardware limit blind spot—using a mathematical method to map their results to a unified, standardized numerical range (e.g., 0 to 1). The specific formula for joint calculation and normalization is as follows: This formula uses the natural exponential function to express time-dimension quantities. Mapped to The dimensionless coefficient of the interval, and then compared with the dimensionless coefficient of the other interval. Multiplication and fusion are performed to ensure that the contributions of the two indicators to the final safety margin coefficient are reasonably reflected, and a uniquely determined implementation method is provided to ensure that indicators with different dimensions and numerical ranges can be effectively fused. The maximum velocity of the target's local trajectory segment when it approaches 0. The collapse decays nonlinearly and exponentially, describing the dynamic safety margin coefficient. Maximum speed of AGV trolley The regulatory mechanism.

[0085] when A higher value indicates sufficient safety margin, and the maximum speed can be maintained near the design value; while when When the value gradually decreases and approaches 0, the maximum speed The AGV rapidly decreases speed in a non-linear, exponential manner. This non-linear decay mechanism ensures that the AGV can quickly and significantly reduce its speed in critical situations where safety risks increase sharply, thereby avoiding collisions or loss of control. This decay method is more aggressive and safer than linear decay.

[0086] The ratio of the remaining collision avoidance redundancy distance to the preset parking clearance, fed back in real time by the AGV's collision avoidance sensors, directly reflects the collision risk of the AGV in the current environment, providing a quantitative basis for safety at the environmental perception level. Simultaneously, by predicting the time required for the steering axis to reach its hardware limit blind spot, the physical limits of the AGV's steering mechanism are taken into account, providing early warning for safety at the mechanical execution level. These two key indicators, through joint calculation and normalization, form a comprehensive and representative dynamic safety margin coefficient. In the maximum speed safety margin control module, this dynamic safety margin coefficient As one of the core inputs to the maximum velocity optimization model, it is related to the system manifold conformity coefficient. and the design maximum speed of local trajectory segments Together they determine the maximum velocity of the target's local trajectory segment. Especially important is the dynamic safety margin coefficient. When the speed approaches zero, meaning the AGV faces extremely high collision risk or mechanical limits, the maximum speed optimization model triggers a non-linear exponential collapse decay mechanism, causing the maximum speed of the target local trajectory segment to decrease. This rapid and significant reduction in speed, along with its nonlinear response mechanism, allows AGVs to quickly and smoothly decrease their speed even under conditions of extremely low safety margins. This avoids the risk of collisions caused by inertia, thereby significantly improving the system's active safety protection capabilities under extreme conditions while ensuring operational efficiency. This dynamic and nonlinear speed control method overcomes the limitations of traditional systems that rely solely on static parameters or simple speed limits, enabling AGVs to cope with complex and ever-changing operating environments more intelligently and safely.

[0087] By introducing a dynamic safety margin coefficient and comprehensively considering the ratio of the remaining collision avoidance redundancy distance fed back by the AGV's collision avoidance sensors to the preset parking clearance, as well as the predicted time for the steering axis to reach the hardware limit blind spot, this application constructs a dual safety evaluation system covering environmental perception and mechanical state. Especially under conditions of extremely low safety margin, through a nonlinear exponential collapse decay speed control mechanism, the AGV can rapidly and significantly reduce its operating speed, thereby effectively avoiding the risk of collisions caused by inertia and significantly improving the AGV's active safety protection capability and operational reliability in complex and variable operating environments.

[0088] The specific steps for the data acquisition module to obtain the relative geometric distance deviation between vehicles and the formation shear deformation angle include: E1: Pre-identify the geometric constraints between multiple vehicles and allow the visual focus set by the director to be used as the virtual geometric center of the corresponding performance group. Establish a formation reference frame for each group with the virtual geometric center as the origin. E2: Convert the absolute trajectory points of each AGV vehicle into polar coordinates relative to the virtual geometric center; E3: Extract the actual rigid geometric relationship of each workshop based on polar coordinate description, and subtract the actual rigid geometric relationship from the design datum to calculate the relative geometric distance deviation between vehicles and the formation shear deformation angle.

[0089] The data acquisition module is responsible for obtaining various real-time data from the AGV platoon and its operating environment. This module can be implemented in several ways, such as utilizing the GPS (Global Positioning System) mounted on the AGV. The system uses inertial measurement units (IMUs), lidar, or vision sensors to directly acquire information such as the absolute position, attitude, and speed of the AGV (Automated Guided Vehicle), and transmits this data in real time to a host computer for processing via wireless communication networks (such as Wi-Fi or 5G). Furthermore, the data acquisition module can also establish a data interface with the AGV's internal control system to directly read the operating status parameters provided by the controller, thereby obtaining more fundamental and precise operational data.

[0090] Pre-identifying the geometric constraints between multiple AGVs refers to determining the relative positions and topological structure that each AGV should maintain within the formation before or during operation. This can be achieved through pre-defined formation templates, such as defining the ideal relative coordinates or vectors of each AGV in standard formations like straight lines, circles, or V-shapes in the host computer. Alternatively, a graph theory-based approach can be used, abstracting each AGV in the formation as a node and treating their expected relative positions (such as distance and angle) as edges, thereby constructing a formation topology graph from which all necessary geometric constraints can be identified.

[0091] The virtual geometric center is determined by calculating the average of the current absolute positions of all AGVs in the formation. Specifically, to adapt to the visual design requirements of multi-focal scenes on stage (such as group performances), the system supports pre-identifying the group formation and geometric constraints between multiple vehicles. It also allows directors to independently set a visual focus for each performance group, directly using this focus as the virtual geometric center of that group. A local coordinate system parallel to the global coordinate system is then established using this point as the origin as the formation reference frame. This multi-center topology effectively solves the problem that a single geometric center cannot describe multiple complex relationships, balancing the flexibility of stage art design with the rigor of collaborative control. Alternatively, one AGV in the formation can be designated as the lead vehicle, and a virtual center can be calculated using this lead vehicle and the relative position information of other vehicles, establishing the formation reference frame based on this virtual center.

[0092] Converting the absolute trajectory points of each AGV to polar coordinates relative to the virtual geometric center involves transforming the position information of each AGV in the global coordinate system into relative position information expressed as distance (polar radius) and angle (polar angle) with the virtual geometric center as the origin. For example, first, the absolute coordinates of the AGVs are obtained. and the coordinates of the virtual geometric center Then calculate the relative rectangular coordinates. Then convert it to polar coordinates. ,in , This conversion method can more intuitively reflect the relative positions of each AGV in the formation.

[0093] Then, the actual rigid geometric relationships of each workshop are extracted and subtracted from the design datum. Based on the above-described polar coordinates, the actual relative distances and angles between AGVs are calculated and compared with the relative distances and angles in the preset ideal formation to quantify the deviations. For example, for the deviation of the relative geometric distance between vehicles, the polar radius of each AGV relative to the virtual geometric center can be directly compared. With design value The difference, for the formation shear deformation angle, can be calculated by taking the interior angle or relative angle of the triangle formed by any three AGVs and comparing it with the corresponding angle in the designed formation, or by comparing the polar angles of each AGV relative to the virtual geometric center. The relative relationship between them and the deviation from the design value.

[0094] By pre-identifying the geometric constraints of multiple workshops, the topological structure of the formation in space can be clearly defined, providing a consistent geometric logic for subsequent collaborative control. A formation reference frame with the virtual geometric center as the origin is established, freeing each AGV from its independent individual coordinate system and mapping it uniformly to a global reference system. This ensures the consistency of the overall movement of the formation. The absolute trajectory points of each AGV are converted into polar coordinates relative to the virtual geometric center. This conversion process leverages the advantages of polar coordinates in describing rotation and distance relationships, providing a more intuitive and accurate reflection of the position of each AGV within the formation. This allows the calculation of inter-vehicle relative geometric distance deviations and formation shear deformation angles to be quantified based on the global reference, rather than relying on the individual vehicle's posture. This effectively eliminates trajectory vector rotation errors caused by posture angle differences, ensuring that the formation can be calibrated in real-time and maintain preset rigid geometric relationships during dynamic operation. This significantly improves the accuracy and reliability of the global formation rigidity collaborative evaluation module, enabling the AGV host computer control system to more effectively maintain and optimize the formation, and enhancing the system's robustness in complex environments.

[0095] After receiving the maximum speed of the target local trajectory segment, the AGV's host computer, combined with the preset initial velocity, final velocity, acceleration, and deceleration parameters, recalculates the acceleration segment distance and deceleration segment distance, and generates a segmented motion execution command with continuous speed and no sudden changes in acceleration segment-uniform speed segment-deceleration segment.

[0096] Specifically, the AGV's host computer receives the maximum speed of the target local trajectory segment. This maximum speed is the highest speed that the AGV formation is allowed to run on in that trajectory segment under a comprehensive evaluation of various factors such as the current operating status, environmental physical disturbances, and electromechanical link steady state. The host computer receives this maximum speed either through wireless communication methods such as Ethernet or Wi-Fi from the slave computer or the central control server, or it can be directly generated by the decision module inside the host computer based on real-time evaluation results and transmitted to the motion planning module.

[0097] After receiving the maximum speed of the target local trajectory segment, the host computer needs to combine the preset initial velocity, final velocity, acceleration and deceleration parameters to define the motion characteristics of the AGV on a specific task or trajectory segment. The initial velocity is the speed when the AGV enters the current trajectory segment, the final velocity is the speed when leaving the current trajectory segment, and the acceleration and deceleration limit the rate of change of the AGV speed. These parameters can be stored in the configuration database of the host computer and dynamically loaded according to the current task type, AGV load, or operation mode.

[0098] Subsequently, the host computer will recalculate the acceleration and deceleration distances. This process is crucial for achieving a smooth speed transition. After receiving the target maximum speed, the system needs to accurately calculate the acceleration distance required for the AGV to reach the target maximum speed, and the deceleration distance required to decelerate from the target maximum speed to the final speed, based on the AGV's current motion state (initial speed), the target maximum speed, and preset acceleration / deceleration parameters. This ensures that the AGV's speed change is continuous and predictable throughout the entire motion. The recalculation of acceleration and deceleration distances can be achieved using classic kinematic formulas, such as... and Iterative calculations can be performed by combining time or distance constraints; alternatively, S-shaped or trapezoidal velocity curve planning algorithms based on time or distance can be used to determine the lengths of acceleration and deceleration segments by solving polynomial equations or piecewise functions.

[0099] Ultimately, the host computer generates segmented motion execution instructions with continuous and abrupt acceleration, constant speed, and deceleration segments. This is the final output of motion planning, aiming to transform abstract speed instructions into motion instructions with smooth speed curves that the AGV can directly execute. By dividing the entire motion process into three stages—acceleration, constant speed, and deceleration—and ensuring the continuity of speed and acceleration between each stage, mechanical shocks and motion instability can be effectively avoided. These instructions can contain discrete point sequences containing information such as timestamps, target speeds, and target positions, collectively defining a smooth speed curve; or they can generate parameterized motion instructions, such as specifying the initial speed, target speed, acceleration, deceleration, and the duration or distance of each segment, which are then interpolated in real time by the AGV lower-level controller to generate a detailed motion trajectory.

[0100] The AGV host computer first receives the maximum speed of the target local trajectory segment calculated by the aforementioned AGV host computer control system (based on multi-dimensional evaluation of the AGV formation's operating status data, mechanical response data, and environmental physical disturbance data). This maximum speed is derived by comprehensively considering factors such as formation rigidity, trajectory fidelity, electromechanical steady state, and environmental disturbances, and represents the highest speed at which the current AGV formation can operate safely and stably on a specific trajectory segment. In order to convert this target maximum speed into smooth motion that the AGV can execute, the host computer further combines preset initial velocity, final velocity, acceleration, and deceleration parameters. These parameters define the basic dynamic characteristics and safety limits of the AGV during motion. Based on the received target maximum speed and preset motion parameters, the host computer accurately recalculates the acceleration distance required for the AGV to accelerate from the initial velocity to the target maximum speed, and the deceleration distance required to decelerate from the target maximum speed to the final velocity. This calculation process ensures the smoothness of speed changes and avoids sudden speed changes.

[0101] Finally, based on the calculated acceleration segment distance, deceleration segment distance, and remaining constant speed segment distance, the host computer generates segmented motion execution instructions for continuous and abrupt acceleration-constant speed-deceleration segments. These instructions are then sent to the AGV (Automated Guided Vehicle), guiding it to move along a predetermined smooth speed curve. In this way, the maximum dynamically adjusted speed provided by the AGV's host computer control system can be executed smoothly and continuously by the AGV, fully leveraging the advantages of dynamic speed control while avoiding mechanical shocks and formation instability caused by sudden speed changes.

[0102] In summary, this application first establishes a formation reference frame with the virtual geometric center as the origin, and converts the absolute trajectory points of each AGV vehicle into polar coordinates relative to this center. Secondly, the inter-vehicle geometric deviation, trajectory tracking error, and underlying servo / synchronization electrical signals are processed to be dimensionless, and the rigid coordination, trajectory fidelity and electromechanical steady-state coefficients are extracted. Finally, based on the above coefficients, the actual ground slip rate and the real-time torque load rate of the steering wheel are used as exponential terms for dimensionality reduction coupling, and combined with the dynamic safety margin coefficient that includes collision avoidance redundancy and mechanical blind spot prediction, a maximum speed optimization model is constructed.

[0103] Through the above-mentioned technical methods, it is possible to perceive in real time and with keen sensitivity the global formation distortion, spatial trajectory deviation and underlying electromechanical health status of AGV formation in complex physical environments; and when faced with external physical disturbances or reduced safety margins, it can adaptively and dynamically adjust the maximum speed of the target local trajectory segment, and then recalculate the acceleration and deceleration distances in combination with preset parameters, and generate a segmented motion execution command of acceleration segment-uniform speed segment-deceleration segment with continuous speed and no sudden changes, which is then sent to the vehicle for execution.

[0104] This application employs a virtual geometric center and polar coordinate transformation mechanism to completely decouple the attitude differences of individual vehicles from the global rigid geometric relationship at the data extraction source. This directly eliminates trajectory vector rotation errors and overcomes the inherent defect of existing technologies that lack a global maintenance mechanism, leading to systemic formation drift. This ensures the consistency of multi-vehicle collaborative execution.

[0105] This application uses spatial trajectory fidelity and electromechanical link steady-state coefficient as the base, and introduces actual ground slippage rate and steering wheel torque load rate as exponential penalty terms into the evaluation system. When facing complex working conditions such as slippery ground or excessive steering load, external disturbances can exponentially amplify their impact on internal trajectory and electromechanical steady state, thus accurately quantifying the negative interference of the external environment on the health status of AGV operation.

[0106] This application exponentially couples the dynamic safety margin coefficient with the system operating state. When the safety margin approaches 0, the target maximum speed triggers a nonlinear exponential collapse decay, rapidly and significantly reducing the speed to avoid potential collisions. At the same time, to avoid formation instability caused by a cliff-like deceleration, the host computer regenerates segmented execution instructions with continuous speed without sudden changes, resolving the technical contradiction between extreme safety obstacle avoidance (requiring extremely fast response) and mechanical operation stability (requiring avoidance of mechanical impact), and endowing the AGV formation with active safety protection capabilities in complex and ever-changing environments.

[0107] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. An AGV (Automated Guided Vehicle) trolley host computer control system, characterized in that, include: The data acquisition module is used to acquire real-time operating status data, mechanical response data, and environmental physical disturbance data of the AGV convoy; The environmental physical disturbance data includes the actual ground slip rate and the real-time torque load rate of the steering wheel. The global formation rigidity cooperative evaluation module is used to construct a global formation rigidity cooperative model and obtain the global formation rigidity cooperative coefficient by using the dynamic integral values ​​of the inter-vehicle relative geometric distance deviation, formation shear deformation angle and attitude deviation angle obtained in real time by the positioning system and attitude sensors. The spatial trajectory fidelity evaluation module is used to construct a spatial trajectory fidelity model and obtain spatial trajectory fidelity coefficients by using the lateral tracking error of the B-spline curve, the out-of-tolerance value of the motion following position, and the absolute zero position offset of the steering wheel obtained by the positioning sensor and the angle sensor. The electromechanical link steady-state evaluation module is used to construct an electromechanical link steady-state model and obtain electromechanical link steady-state coefficients by monitoring and acquiring the transient voltage drop of the servo bus, the multi-axis synchronization time deviation, and the dead zone ionization of the analog input of the joystick through the underlying hardware sensors. The system manifold conformance calculation module is used to obtain the system manifold conformance coefficient by performing exponential dimensionality reduction coupling based on the spatial trajectory fidelity coefficient and the electromechanical link steady-state coefficient, combined with the environmental physical disturbance data. The maximum speed safety margin control module is used to construct a maximum speed optimization model based on the system manifold conformity coefficient, the design maximum speed of the local trajectory segment, and the dynamic safety margin coefficient, output the maximum speed of the target local trajectory segment, and send it to the AGV for execution.

2. The AGV trolley host computer control system according to claim 1, characterized in that: The method for obtaining the global formation rigidity coordination coefficient in the global formation rigidity coordination evaluation module includes: A1: After obtaining the instantaneous attitude deviation by comparing the real-time attitude angle of the AGV with the expected attitude angle, the dynamic integral value of the attitude deviation angle is obtained by performing an integral calculation within a preset time window. A2: Calculate the ratio of the dynamic integral values ​​of the relative geometric distance deviation between vehicles, the formation shear deformation angle, and the attitude deviation angle to their respective reference thresholds for dimensionless processing. A3: The reference thresholds include relative distance allowable reference threshold, shear angle allowable reference threshold and attitude angle integral reference threshold respectively; A4: Squaring each ratio after dimensionless processing, multiplying each by the corresponding normalized weighting coefficient, and then summing the results; the sum of the normalized weighting coefficients is limited to one. A5: Perform a square root operation on the summation result to obtain the comprehensive error norm; A6: The negative value of the comprehensive error norm is used as the exponent of the natural exponential function to calculate the global formation rigidity coordination coefficient that decays continuously in the interval (0,1).

3. The AGV trolley host computer control system according to claim 2, characterized in that: The method for obtaining the spatial trajectory fidelity evaluation module includes: B1: The lateral tracking error of the B-spline curve is calculated by obtaining the global coordinates of the vehicle through the positioning sensor and combining them with the preset mathematical model of the B-spline curve; The motion tracking position deviation value is obtained by comparing the theoretical position calculated by odometry integration with the actual positioning position; The absolute zero offset of the steering wheel is obtained by measuring the actual angle using a steering wheel encoder or angle sensor and comparing it with the theoretical zero position. B2: Calculate the ratio of the lateral tracking error of the B-spline curve, the out-of-tolerance value of the motion following position, and the absolute zero position offset of the steering wheel to their respective tolerance thresholds, and perform dimensionless processing. The tolerance thresholds include lateral error tolerance, out-of-tolerance limit threshold, and zero-position deviation tolerance threshold, respectively. B3: Calculate the nonlinear even powers of each ratio after dimensionless processing to obtain the exponential penalty value of each parameter; B4: Summing the exponential penalty values ​​of each parameter to obtain the polynomial error accumulation value, and then taking the reciprocal of the polynomial error accumulation value after adding one to it to calculate the spatial trajectory fidelity coefficient.

4. The AGV trolley host computer control system according to claim 3, characterized in that... In the electromechanical link steady-state evaluation module, the steady-state coefficients of the electromechanical link are obtained. The model formula is: In the formula, For the transient voltage drop of the servo bus, The undervoltage alarm threshold; For multi-axis synchronization time deviation, This represents the upper limit of the synchronization time tolerance. The analog input for the joystick is the dead zone detachment degree. This is the noise floor filtering threshold; , , All are sensitivity gain constants; The transient voltage drop of the servo bus is calculated by monitoring the voltage value on the DC bus of the servo driver; the multi-axis synchronization time deviation is obtained by comparing the sending and execution times of motion commands recorded by the timestamp module; and the dead zone ionization is obtained by continuously collecting data from the analog-to-digital converter when the joystick is stationary and calculating the peak-to-peak value of the fluctuation range.

5. The AGV trolley host computer control system according to claim 4, characterized in that: In the system manifold conformity calculation module, the system manifold conformity coefficient is obtained. The model formula is: In the formula, The fidelity coefficient of the spatial trajectory; The steady-state coefficient of the electromechanical link; The actual ground slip rate; The real-time torque load rate of the steering wheel; and All are physical disturbance intensity penalty constants, and and The range of values ​​is all within between; The actual ground slip rate is calculated by comparing the rotational speed of the AGV's drive wheels with the actual vehicle speed; the real-time torque load rate of the steering wheel is obtained by monitoring the motor's output torque using a current sensor or torque sensor on the motor and comparing it with the maximum rated torque.

6. The AGV trolley host computer control system according to claim 5, characterized in that: The method for outputting the maximum speed of the target local trajectory segment in the maximum speed safety margin control module includes: C1: Based on the safety redundancy state reflected by the dynamic safety margin coefficient, reverse risk correlation is performed, and nonlinear sensitivity weighting and exponential mapping are performed in combination with the cliff braking slope factor to obtain a dynamic safety power exponent used to quantitatively characterize the deterioration trend of space safety risks. C2: Based on the dynamic safety power exponent, the form-preserving coefficient of the system manifold is subjected to nonlinear power function decay constraint to obtain the form-preserving nonlinear decay factor used to comprehensively characterize the coupling characteristics of the system's steady-state operation and external risks; C3: Utilize the shape-preserving nonlinear decay factor to dynamically and adaptively limit and control the maximum speed of the local trajectory segment, and obtain and output the maximum speed of the target local trajectory segment.

7. The AGV trolley host computer control system according to claim 6, characterized in that: The method for obtaining the dynamic safety margin coefficient is as follows: D1: Obtain the ratio of the remaining anti-collision redundancy distance to the preset parking limit fed back by the AGV anti-collision sensor and the predicted time for the steering axis to reach the hardware limit dead angle, and perform joint calculation through the normalization formula; The normalization formula is: in, For dynamic safety margin coefficient, The percentage of the remaining collision avoidance redundancy distance relative to the preset parking clearance. $ represents the predicted time for the steering shaft to reach the hardware's maximum dead angle. This is the preset safety response time constant; D2: When the dynamic safety margin coefficient approaches 0, the nonlinear decay factor of the conformity is triggered, driving the maximum velocity of the target local trajectory segment to decay nonlinearly and exponentially.

8. The AGV trolley host computer control system according to claim 7, characterized in that: The specific steps for the data acquisition module to obtain the relative geometric distance deviation between vehicles and the formation shear deformation angle include: E1: Pre-identify the geometric constraints between multiple vehicles and establish a formation reference frame with the virtual geometric center as the origin; E2: Convert the absolute trajectory points of each AGV vehicle into polar coordinates relative to the virtual geometric center; E3: Extract the actual rigid geometric relationship of each workshop based on the polar coordinate description, and subtract the actual rigid geometric relationship from the design benchmark to calculate the relative geometric distance deviation between vehicles and the formation shear deformation angle.

9. The AGV trolley host computer control system according to claim 8, characterized in that: After receiving the maximum speed of the target local trajectory segment, the AGV host computer, combined with the preset initial velocity, final velocity, acceleration and deceleration parameters, recalculates the acceleration segment distance and deceleration segment distance, and generates a segmented motion execution command with continuous speed and no sudden changes in acceleration segment-uniform speed segment-deceleration segment.

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