A high-efficiency gait control method for a four-legged robot dog based on biomechanical principles

Abstract

This invention discloses an efficient gait control method for a quadruped robot dog based on biomechanical principles. By collecting and analyzing the gait characteristics of quadruped animals in nature, a more realistic reference can be provided for the design of the quadruped robot dog, making its gait closer to nature and improving the smoothness and stability of walking. By optimizing the gait model using simulation technology, an efficient and energy-saving gait pattern can be obtained, reducing energy consumption and improving walking speed and efficiency. At the same time, considering the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized through a gait generation algorithm to adapt it to different physical structures and movement capabilities, maintaining stable walking in complex environments. By applying specific calculation formulas and adjusting algorithm parameters, the energy consumption per step can be significantly reduced, improving overall energy efficiency. Multiple movement patterns can be generated to adapt to different environments and task requirements, effectively improving the robot dog's walking efficiency and reducing unnecessary energy consumption and movements.

Description

Technical Field

[0001] This invention relates to the field of gait control technology for quadruped robot dogs, and more particularly to an efficient gait control method for quadruped robot dogs based on biomechanical principles. Background Technology

[0002] As an important branch of modern robotics technology, the motion control and gait optimization of quadrupedal robot dogs have always been a hot topic and a challenge in the research field. Most traditional quadrupedal robot dog gait control methods are based on preset gait patterns and fixed control strategies. These methods often show great limitations when dealing with complex and ever-changing environments and task requirements.

[0003] Quadrupeds in nature, such as dogs, cats, and horses, have evolved gait patterns over millions of years to adapt to various terrains and task requirements. These gait patterns not only possess efficient and stable movement characteristics but also can adaptively adjust to different environmental and task conditions. Therefore, drawing inspiration and reference from the gait characteristics of quadrupeds in nature can provide valuable insights for the gait control of quadrupedal robotic dogs. Summary of the Invention

[0004] In view of this, the present invention proposes an efficient gait control method for quadruped robot dogs based on biomechanical principles, which can effectively solve the limitations of existing technologies in dealing with complex and ever-changing environments and task requirements.

[0005] The technical solution of this invention is implemented as follows:

[0006] A biomechanically based, efficient gait control method for a quadruped robot dog includes:

[0007] We collected and analyzed the gait characteristics of tetrapods in nature, and used biomechanical principles to construct a gait model of a quadruped robot dog.

[0008] Based on the gait model, the gait pattern of the quadruped robot dog is optimized through simulation technology to obtain the initial gait pattern of the quadruped robot dog.

[0009] Based on the gait generation algorithm and the hardware characteristics of the quadruped robot dog, the initial gait pattern of the quadruped robot dog is optimized to obtain the final gait pattern of the quadruped robot dog.

[0010] Gait control of the quadruped robot dog is performed based on the final quadruped robot dog gait pattern;

[0011] The gait generation algorithm uses the following calculation formula when optimizing the initial gait pattern:

[0012]

[0013] The Eopt E represents the optimized single-step energy consumption. kin E represents the kinetic energy consumption of the robot dog in a single step. pot This represents the change in potential energy of the robot dog in a single step, where β is the potential energy influence coefficient, and T... step T represents the single-step time of the current gait. ref The single-step time is used as a reference gait.

[0014] As a further optional solution to the aforementioned efficient gait control method for a quadruped robot dog based on biomechanical principles, the step of collecting and analyzing the gait characteristics of quadruped animals in nature and constructing a gait model of the quadruped robot dog using biomechanical principles specifically includes:

[0015] Acquire gait data of tetrapods under different terrain, speed and task conditions;

[0016] Gait features are extracted from gait data, including joint angle changes and limb movement trajectories during the gait cycle;

[0017] Statistical analysis was performed on the extracted gait features to obtain the relationship between gait features and animal movement performance, including gait frequency and speed, stride length and stability.

[0018] Based on biomechanical principles and the analysis results of quadrupedal animal gait characteristics, a gait model of a quadrupedal robot dog was constructed.

[0019] As a further optional solution to the aforementioned efficient gait control method for a quadruped robot dog based on biomechanical principles, the gait model of the quadruped robot dog, constructed based on biomechanical principles and combined with the analysis results of quadrupedal animal gait characteristics, specifically includes:

[0020] Based on the analysis of kinematic principles and the gait characteristics of quadrupedal animals, the kinematic relationships between the joints of a quadrupedal robot dog are established, including forward kinematics and inverse kinematics.

[0021] Based on the analysis results of dynamic principles and quadrupedal gait characteristics, the force situation of the quadrupedal robot dog during movement is analyzed, and dynamic equations are established.

[0022] By integrating the kinematic and dynamic models, a gait model for the quadruped robot dog is obtained.

[0023] As a further optional solution to the biomechanically based quadruped robot dog efficient gait control method, the step of optimizing the quadruped robot dog's gait pattern through simulation technology based on the gait model to obtain the initial gait pattern of the quadruped robot dog specifically includes:

[0024] Build a virtual model of the quadruped robot dog in the simulation tool and set the simulation environment parameters;

[0025] The gait model is imported into the simulation environment, allowing the quadruped robot dog to move according to the gait model in the virtual environment.

[0026] During the simulation, motion data of the quadruped robot dog is collected, including joint angles, velocity, acceleration, and ground reaction force.

[0027] The collected motion data is analyzed, and based on the analysis results, the gait model parameters are optimized to obtain the optimal gait parameters;

[0028] Based on the gait model with optimal gait parameters, the initial gait pattern of the quadruped robot dog is obtained.

[0029] As a further optional solution to the biomechanically based quadruped robot dog efficient gait control method, the β value is set and adjusted according to the specific hardware characteristics and task requirements of the quadruped robot dog, specifically including:

[0030] Obtain the hardware characteristic parameters of the quadruped robot dog, including the joint performance, limb structure, and drive system of the quadruped robot dog;

[0031] Obtain task requirement parameters, including movement speed, stability requirements, and energy consumption limits;

[0032] Obtain environmental constraint parameters, including terrain complexity, ground material, and weather conditions;

[0033] The β value is determined based on the hardware characteristics, task requirements, and environmental constraints of the quadruped robot dog.

[0034] As a further optional solution to the aforementioned efficient gait control method for a quadruped robot dog based on biomechanical principles, the method further includes real-time monitoring of the robot dog's motion state and external environmental information, specifically including:

[0035] Sensors, including position sensors, force sensors, vision sensors, and environmental sensors, are installed on the quadruped robot dog.

[0036] Utilize sensors to perform real-time position and attitude monitoring, motion status monitoring, and external environment monitoring;

[0037] Data from different sensors is fused and processed to form comprehensive monitoring information.

[0038] As a further optional embodiment of the biomechanically based quadruped robot dog efficient gait control method, the method further includes:

[0039] Based on preset alarm thresholds and comprehensive monitoring information, the robot dog's movement status and environmental parameters are monitored in real time to check for any abnormalities. When an abnormality occurs, an alarm signal is issued, and the time, location, and specific information of the abnormality are recorded.

[0040] A high-efficiency gait control system for a quadruped robot dog based on biomechanical principles includes:

[0041] Gait feature acquisition and analysis module: used to collect and analyze the gait features of quadruped animals in nature, and to construct a gait model of a quadruped robot dog using biomechanical principles;

[0042] Gait model simulation optimization module: Based on the gait model, the gait pattern of the quadruped robot dog is optimized through simulation technology to obtain the initial gait pattern of the quadruped robot dog;

[0043] Gait pattern optimization module: Based on the gait generation algorithm and combined with the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized to obtain the final quadruped robot dog gait pattern;

[0044] Gait control module: Controls the gait of the quadruped robot dog based on the final gait pattern;

[0045] The gait generation algorithm uses the following calculation formula when optimizing the initial gait pattern:

[0046]

[0047] The E opt E represents the optimized single-step energy consumption. kin E represents the kinetic energy consumption of the robot dog in a single step. pot This represents the change in potential energy of the robot dog in a single step, where β is the potential energy influence coefficient, and T... step T represents the single-step time of the current gait. ref The single-step time is used as a reference gait.

[0048] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the biomechanical principle-based efficient gait control method for quadrupedal robot dogs described above.

[0049] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the biomechanical-based efficient gait control method for quadrupedal robot dogs described above.

[0050] The beneficial effects of this invention are as follows: By collecting and analyzing the gait characteristics of quadrupedal animals in nature, the walking patterns of quadrupedal animals can be simulated more accurately, providing a more realistic reference for the design of quadrupedal robot dogs. This makes the gait of the quadrupedal robot dog closer to nature, thereby improving its walking smoothness and stability. Optimizing the gait model using simulation technology can yield a more efficient and energy-saving gait pattern. The optimized gait pattern can reduce the energy consumption of the quadrupedal robot dog during walking, while improving its walking speed and efficiency. Furthermore, by considering the hardware characteristics of the quadrupedal robot dog and optimizing the initial gait pattern through a gait generation algorithm, the final gait pattern can better adapt to the quadrupedal robot dog's needs. The robot dog's physical structure and movement capabilities, along with its highly adaptable gait pattern, enable it to maintain stable walking in various complex environments. Furthermore, by applying specific calculation formulas to optimize the initial gait pattern, the optimized gait pattern significantly reduces the energy consumption per step during walking, thereby improving its overall energy efficiency. By adjusting the parameters in the gait generation algorithm, this technical solution allows the robot dog to adapt to different walking environments and task requirements. It not only optimizes the energy consumption of a single step but also allows for the generation of multiple different movement patterns by adjusting algorithm parameters. Through gait pattern optimization, this technical solution can improve the robot dog's walking efficiency and reduce unnecessary energy consumption and movements. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0052] Figure 1 This is a flowchart illustrating an efficient gait control method for a quadruped robot dog based on biomechanical principles, according to the present invention.

[0053] Figure 2 This is a schematic diagram of the composition of a high-efficiency gait control system for a quadruped robot dog based on biomechanical principles according to the present invention.

[0054] Figure 3 This is a schematic diagram of the composition of a computing device according to the present invention. Detailed Implementation

[0055] The technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] refer to Figures 1 to 3 A method for efficient gait control of a quadruped robot dog based on biomechanical principles, comprising:

[0057] We collected and analyzed the gait characteristics of tetrapods in nature, and used biomechanical principles to construct a gait model of a quadruped robot dog.

[0058] Based on the gait model, the gait pattern of the quadruped robot dog is optimized through simulation technology to obtain the initial gait pattern of the quadruped robot dog.

[0059] Based on the gait generation algorithm and the hardware characteristics of the quadruped robot dog, the initial gait pattern of the quadruped robot dog is optimized to obtain the final gait pattern of the quadruped robot dog.

[0060] Gait control of the quadruped robot dog is performed based on the final quadruped robot dog gait pattern;

[0061] The gait generation algorithm uses the following calculation formula when optimizing the initial gait pattern:

[0062]

[0063] The E opt E represents the optimized single-step energy consumption. kin E represents the kinetic energy consumption of the robot dog in a single step. pot This represents the change in potential energy of the robot dog in a single step, where β is the potential energy influence coefficient, and T... step T represents the single-step time of the current gait. ref The single-step time is used as a reference gait.

[0064] In this embodiment, by collecting and analyzing the gait characteristics of quadrupedal animals in nature, the walking patterns of quadrupedal animals can be simulated more accurately, providing a more realistic reference for the design of the quadrupedal robot dog. This makes the gait of the quadrupedal robot dog closer to nature, thereby improving its walking smoothness and stability. Optimizing the gait model using simulation technology yields a more efficient and energy-saving gait pattern. The optimized gait pattern reduces the energy consumption of the quadrupedal robot dog during walking, while improving its walking speed and efficiency. Furthermore, by considering the hardware characteristics of the quadrupedal robot dog, the initial gait pattern is optimized through a gait generation algorithm, making the final gait pattern better suited to the quadrupedal robot dog. The physical structure and movement capabilities of the quadruped robot dog enable it to maintain stable walking in various complex environments. Furthermore, by applying specific calculation formulas to optimize the initial gait pattern, the optimized gait pattern significantly reduces the energy consumption per step during walking, thereby improving its overall energy efficiency. By adjusting the parameters in the gait generation algorithm, this technology allows the robot dog to adapt to different walking environments and task requirements. It not only optimizes the energy consumption of a single step but also allows for the generation of multiple different movement patterns by adjusting algorithm parameters. By optimizing the gait pattern, this technology can improve the robot dog's walking efficiency and reduce unnecessary energy consumption and movements.

[0065] It should be noted that by leveraging the hardware characteristics of the quadruped robot dog, we can analyze the energy changes in its initial gait pattern. By analyzing and adjusting these energy changes through a gait generation algorithm, we can obtain the lowest energy consumption gait pattern that allows the quadruped robot dog to maintain stable walking in various complex environments.

[0066] Preferably, the step of collecting and analyzing the gait characteristics of tetrapods in nature and constructing a gait model of a quadruped robot dog using biomechanical principles specifically includes:

[0067] Acquire gait data of tetrapods under different terrain, speed and task conditions;

[0068] Gait features are extracted from gait data, including joint angle changes and limb movement trajectories during the gait cycle;

[0069] Statistical analysis was performed on the extracted gait features to obtain the relationship between gait features and animal movement performance, including gait frequency and speed, stride length and stability.

[0070] Based on biomechanical principles and the analysis results of quadrupedal animal gait characteristics, a gait model of a quadrupedal robot dog was constructed.

[0071] In this embodiment, by acquiring gait data of quadrupeds under different terrain, speed, and task conditions, a comprehensive understanding of the walking characteristics of quadrupeds in different environments can be achieved. The comprehensiveness of the data helps to construct a more accurate and adaptable quadruped robot dog gait model. Gait features extracted from the gait data, such as joint angle changes and limb movement trajectories, are key information for constructing the gait model. Accurate extraction of these features ensures that the gait model is highly consistent with the actual walking behavior of quadrupeds, thereby improving the model's effectiveness. Statistical analysis of the extracted gait features reveals the relationship between gait features and animal motor performance, such as stride frequency and speed, stride length and stability. This study helps to rationally set gait parameters according to the actual needs of quadruped robot dogs when constructing gait models, so as to achieve the best walking effect. By combining biomechanical principles and analyzing the gait characteristics of quadrupeds, the study can reveal the mechanical mechanisms and energy conversion laws in their walking process. This helps to simulate a more realistic and efficient walking mode when constructing gait models for quadruped robot dogs, thereby improving the walking efficiency and stability of robot dogs. The gait model constructed based on biomechanical principles and the analysis results of quadruped gait characteristics has high practicality and reliability. This model can guide the walking strategies of quadruped robot dogs in different environments, enabling them to adapt to various complex terrains and task requirements.

[0072] Preferably, the construction of the gait model of the quadruped robot dog based on biomechanical principles and the analysis results of quadruped gait characteristics specifically includes:

[0073] Based on the analysis of kinematic principles and the gait characteristics of quadrupedal animals, the kinematic relationships between the joints of a quadrupedal robot dog are established, including forward kinematics and inverse kinematics.

[0074] Based on the analysis results of dynamic principles and quadrupedal gait characteristics, the force situation of the quadrupedal robot dog during movement is analyzed, and dynamic equations are established.

[0075] By integrating the kinematic and dynamic models, a gait model for the quadruped robot dog is obtained.

[0076] In this embodiment, by utilizing kinematic principles and the analysis results of quadrupedal gait characteristics, this technical solution can accurately establish the kinematic relationships between the joints of the quadrupedal robot dog. This includes forward kinematics (calculating the position and orientation of the end effector based on joint angles) and inverse kinematics (calculating joint angles based on the position and orientation of the end effector). Precise kinematic relationships help ensure coordinated movement of the joints during walking, thereby improving walking stability and efficiency. Based on the analysis results of dynamic principles and quadrupedal gait characteristics, this technical solution can deeply analyze the forces acting on the quadrupedal robot dog during movement, including gravity, ground reaction force, inertial force, etc., and how these forces affect the robot dog's motion state and gait. By establishing dynamic equations, the quadrupedal robot dog can be more accurately predicted and controlled. This technology improves the gait of quadrupedal robot dogs by integrating kinematic and dynamic models. This integration considers not only the kinematic relationships between the joints but also the forces acting on the robot during movement. Optimizing the gait model further enhances the robot dog's walking performance, including increasing walking speed, reducing energy consumption, and improving stability. This technical solution not only provides a scientific gait model for quadrupedal robot dogs but also lays the foundation for their intelligent control. By combining the gait model with sensors, controllers, and other hardware, the quadrupedal robot dog can achieve autonomous navigation, obstacle avoidance, and path planning. This helps improve the robot dog's intelligence and autonomy, enabling it to perform tasks more flexibly and efficiently in complex environments.

[0077] It should be noted that the establishment of the kinematic model includes:

[0078] Forward kinematics: Forward kinematics describes the mapping relationship from joint angles to the position and posture of the end effector (foot). In quadrupedal robot dogs, forward kinematics can be used to calculate the position and posture of the foot in space given each joint angle. This involves the geometric relationship of parameters such as link length and joint angle, and can be achieved through kinematic modeling methods such as DH parameter method, Lie algebra method or spiral theory.

[0079] Inverse kinematics: Inverse kinematics is the process of deriving the angles that each joint should reach from the target position and posture of the end effector (foot). In a quadruped robot dog, inverse kinematics is used to plan the movement trajectory of the foot and calculate the joint angles required to achieve the trajectory.

[0080] The establishment of the dynamic model includes:

[0081] Force analysis: Based on the principles of dynamics, the force situation of the quadruped robot dog during the movement process is analyzed, including gravity, ground reaction force, inertial force, etc. It is necessary to consider the influence of factors such as the mass distribution of the quadruped robot dog, joint stiffness, and ground conditions on the force situation.

[0082] Establishment of dynamic equations: Based on the force analysis, the dynamic equations of the quadruped robot dog are established. This involves dynamic modeling methods such as the Lagrange equation, the Newton-Euler equation, or Hamilton's principle. The dynamic equations describe the relationship between the torque, velocity, and acceleration of each joint of the quadruped robot dog during its movement.

[0083] Preferably, the step of optimizing the gait pattern of the quadruped robot dog based on the gait model using simulation technology to obtain the initial gait pattern of the quadruped robot dog specifically includes:

[0084] Build a virtual model of the quadruped robot dog in the simulation tool and set the simulation environment parameters;

[0085] The gait model is imported into the simulation environment, allowing the quadruped robot dog to move according to the gait model in the virtual environment.

[0086] During the simulation, motion data of the quadruped robot dog is collected, including joint angles, velocity, acceleration, and ground reaction force.

[0087] The collected motion data is analyzed, and based on the analysis results, the gait model parameters are optimized to obtain the optimal gait parameters;

[0088] Based on the gait model with optimal gait parameters, the initial gait pattern of the quadruped robot dog is obtained.

[0089] In this embodiment, the quadruped robot dog virtual model built in the simulation tool can highly reproduce its real physical characteristics and movement mechanism. The simulation environment parameters, such as terrain, friction, and gravity, can simulate various real-world walking scenarios, providing a rich testing environment for gait pattern optimization. By importing the gait model into the simulation environment and allowing the quadruped robot dog to move according to the gait model in the virtual environment, its walking effect can be observed intuitively. By collecting motion data, such as joint angles, velocity, acceleration, and ground reaction force, the performance of the gait model can be comprehensively evaluated. Based on the analysis results, the parameters of the gait model can be optimized to continuously improve the accuracy and adaptability of the gait. The optimal gait parameters are obtained. Based on the gait model with the optimal gait parameters, the initial gait pattern of the quadruped robot dog is obtained, which has high scientific validity and reliability. This initial gait pattern not only conforms to the walking rules of quadruped animals, but also shows good stability and efficiency in practical applications. Optimizing the gait pattern through simulation technology can greatly reduce the number of tests and testing costs of the actual quadruped robot dog. The initial gait pattern obtained through simulation technology can improve the adaptability and performance of the quadruped robot dog in different terrains and scenarios. This optimized gait pattern can make the quadruped robot dog more stable and efficient during walking, reduce energy consumption and wear, and extend its service life.

[0090] Preferably, the β value is set and adjusted according to the specific hardware characteristics and task requirements of the quadruped robot dog, specifically including:

[0091] Obtain the hardware characteristic parameters of the quadruped robot dog, including the joint performance, limb structure, and drive system of the quadruped robot dog;

[0092] Obtain task requirement parameters, including movement speed, stability requirements, and energy consumption limits;

[0093] Obtain environmental constraint parameters, including terrain complexity, ground material, and weather conditions;

[0094] The β value is determined based on the hardware characteristics, task requirements, and environmental constraints of the quadruped robot dog.

[0095] In this embodiment, by acquiring the hardware characteristic parameters of the quadruped robot dog, such as joint performance, limb structure, and drive system, a comprehensive understanding of its physical characteristics and mobility can be obtained. This helps ensure that the β value setting matches the hardware characteristics of the quadruped robot dog, thereby fully leveraging its performance advantages and avoiding waste or overuse of hardware resources. Acquiring task requirement parameters, such as movement speed, stability requirements, and energy consumption limits, clarifies the specific needs of the quadruped robot dog when performing tasks. By adjusting the β value, it can be ensured that the quadruped robot dog meets these requirements during walking, such as increasing movement speed, enhancing stability, and reducing energy consumption. This helps improve the execution efficiency and success rate of the quadruped robot dog in complex tasks. Acquiring environmental constraint parameters, such as ground... By considering factors such as shape complexity, ground material, and weather conditions, we can understand the various challenges that the quadruped robot dog may face during its movement. By adjusting the β value, the quadruped robot dog can better adapt to these environmental constraints, such as maintaining stability on different terrains and operating normally in harsh weather conditions. This helps improve the quadruped robot dog's adaptability and survivability in complex environments. The setting and adjustment of the β value is a dynamic process that requires comprehensive consideration of the quadruped robot dog's hardware characteristics, task requirements, and environmental constraints. By continuously optimizing the β value, the quadruped robot dog's performance can be continuously improved, such as increasing walking efficiency, reducing energy consumption, and enhancing stability. This dynamic adjustment mechanism helps ensure that the quadruped robot dog maintains its optimal state in different scenarios.

[0096] It should be noted that the hardware characteristic parameters for obtaining the quadruped robot dog include:

[0097] Joint performance can be quantified using parameters such as maximum torque, maximum speed, and precision of the joint;

[0098] Limb structure: It can be quantified using parameters such as limb length, mass, and cross-sectional shape;

[0099] Drive system: It can be quantified using parameters such as the power, torque, and speed of the motor, while also considering the transmission ratio and efficiency of the reducer;

[0100] The required parameters for obtaining the task include:

[0101] Movement speed: can be quantified using the desired walking speed;

[0102] Stability requirements: can be quantified using stability indices (such as the projected area of ​​the center of gravity, static stability margin, etc.);

[0103] Energy consumption limitations: These can be quantified using the desired energy consumption level or battery life.

[0104] Obtaining environmental constraint parameters includes:

[0105] Terrain complexity: can be quantified using parameters such as terrain slope, ruggedness, and obstacle density;

[0106] Ground material: can be quantified using parameters such as ground hardness and coefficient of friction;

[0107] Weather conditions: can be quantified using parameters such as temperature, humidity, and wind speed.

[0108] Preferably, the method further includes real-time monitoring of the robot dog's movement status and external environmental information, specifically including:

[0109] Sensors, including position sensors, force sensors, vision sensors, and environmental sensors, are installed on the quadruped robot dog.

[0110] Utilize sensors to perform real-time position and attitude monitoring, motion status monitoring, and external environment monitoring;

[0111] Data from different sensors is fused and processed to form comprehensive monitoring information.

[0112] In this embodiment, by installing various sensors on the quadruped robot dog, including position sensors, force sensors, vision sensors, and environmental sensors, comprehensive real-time monitoring of the robot dog's movement status and external environment can be achieved. These sensors can monitor the robot dog's position and posture, movement status (such as speed, acceleration, joint angles, etc.), and external environmental information (such as terrain, obstacles, weather, etc.). Fusing data from different sensors generates more accurate and comprehensive integrated monitoring information. Data fusion technology comprehensively considers data from various sensors, eliminating errors or uncertainties that may exist with a single sensor, and improving the accuracy and reliability of monitoring information. Real-time monitoring of the robot dog's movement status and external environmental information provides important basis for the robot dog's autonomous navigation. By analyzing this information, the robot dog can autonomously plan its walking path, avoid obstacles, and adapt to different terrains, thereby improving its autonomous navigation capabilities and intelligence level. Real-time monitoring of the robot dog's movement status provides real-time feedback for its motion control. By analyzing the movement status data, potential problems during the robot dog's movement can be identified in a timely manner, such as joint wear, excessive energy consumption, and unstable movement, allowing for corresponding optimization and adjustment measures.

[0113] Preferably, the method further includes:

[0114] Based on preset alarm thresholds and comprehensive monitoring information, the robot dog's movement status and environmental parameters are monitored in real time to check for any abnormalities. When an abnormality occurs, an alarm signal is issued, and the time, location, and specific information of the abnormality are recorded.

[0115] In this embodiment, by using preset alarm thresholds and comprehensive monitoring information, the robot dog's movement status and environmental parameters can be monitored in real time. Once an anomaly is detected, an alarm signal is immediately issued. This immediacy helps to promptly identify and address potential problems, preventing further deterioration and ensuring the robot dog's safety and the smooth execution of tasks. By recording and saving anomaly information, technicians can quickly understand the robot dog's operating status remotely or on-site, reducing troubleshooting time. This not only improves the efficiency of fault handling but also reduces downtime and maintenance costs caused by faults. By analyzing the data and records of anomalies, the operating patterns and potential problems of the robot dog under different environments and usage conditions can be summarized. This information can be used to optimize the machine's maintenance strategy, such as developing more reasonable maintenance plans, adjusting maintenance cycles and repair content, thereby reducing maintenance costs and extending the machine's service life.

[0116] A high-efficiency gait control system for a quadruped robot dog based on biomechanical principles includes:

[0117] Gait feature acquisition and analysis module: used to collect and analyze the gait features of quadruped animals in nature, and to construct a gait model of a quadruped robot dog using biomechanical principles;

[0118] Gait model simulation optimization module: Based on the gait model, the gait pattern of the quadruped robot dog is optimized through simulation technology to obtain the initial gait pattern of the quadruped robot dog;

[0119] Gait pattern optimization module: Based on the gait generation algorithm and combined with the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized to obtain the final quadruped robot dog gait pattern;

[0120] Gait control module: Controls the gait of the quadruped robot dog based on the final gait pattern;

[0121] The gait generation algorithm uses the following calculation formula when optimizing the initial gait pattern:

[0122]

[0123] The E opt E represents the optimized single-step energy consumption. kin E represents the kinetic energy consumption of the robot dog in a single step. pot This represents the change in potential energy of the robot dog in a single step, where β is the potential energy influence coefficient, and T... step T represents the single-step time of the current gait. ref The single-step time is used as a reference gait.

[0124] A computing device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the biomechanical principle-based efficient gait control method for quadrupedal robot dogs described above.

[0125] A computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the biomechanical-based efficient gait control method for quadrupedal robot dogs described above.

[0126] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for efficient gait control of a quadruped robot dog based on biomechanical principles, characterized in that, include: We collected and analyzed the gait characteristics of tetrapods in nature, and used biomechanical principles to construct a gait model of a quadruped robot dog. Based on the gait model, the gait pattern of the quadruped robot dog is optimized through simulation technology to obtain the initial gait pattern of the quadruped robot dog. Based on the gait generation algorithm and the hardware characteristics of the quadruped robot dog, the initial gait pattern of the quadruped robot dog is optimized to obtain the final gait pattern of the quadruped robot dog. Gait control of the quadruped robot dog is performed based on the final quadruped robot dog gait pattern; The gait generation algorithm uses the following calculation formula when optimizing the initial gait pattern: The E opt E represents the optimized single-step energy consumption. kin E represents the kinetic energy consumption of the robot dog in a single step. pot This represents the change in potential energy of the robot dog in a single step, where β is the potential energy influence coefficient, and T... step T represents the single-step time of the current gait. ref The single-step time is used as a reference gait.

2. The efficient gait control method for a quadruped robot dog based on biomechanical principles according to claim 1, characterized in that, The process of collecting and analyzing the gait characteristics of tetrapods in nature, and constructing a gait model of a quadruped robot dog using biomechanical principles, specifically includes: Acquire gait data of tetrapods under different terrain, speed and task conditions; Gait features are extracted from gait data, including joint angle changes and limb movement trajectories during the gait cycle; Statistical analysis was performed on the extracted gait features to obtain the relationship between gait features and animal movement performance, including gait frequency and speed, stride length and stability. Based on biomechanical principles and the analysis results of quadrupedal animal gait characteristics, a gait model of a quadrupedal robot dog was constructed.

3. The efficient gait control method for a quadruped robot dog based on biomechanical principles according to claim 2, characterized in that, Based on biomechanical principles and the analysis results of quadrupedal gait characteristics, a gait model for a quadrupedal robotic dog is constructed, specifically including: Based on the analysis of kinematic principles and the gait characteristics of quadrupedal animals, the kinematic relationships between the joints of a quadrupedal robot dog are established, including forward kinematics and inverse kinematics. Based on the analysis results of dynamic principles and quadrupedal gait characteristics, the force situation of the quadrupedal robot dog during movement is analyzed, and dynamic equations are established. By integrating the kinematic and dynamic models, a gait model for the quadruped robot dog is obtained.

4. The efficient gait control method for a quadruped robot dog based on biomechanical principles according to claim 3, characterized in that, Based on the gait model, the gait pattern of the quadruped robot dog is optimized through simulation technology to obtain the initial gait pattern of the quadruped robot dog, specifically including: Build a virtual model of the quadruped robot dog in the simulation tool and set the simulation environment parameters; The gait model is imported into the simulation environment, allowing the quadruped robot dog to move according to the gait model in the virtual environment. During the simulation, motion data of the quadruped robot dog is collected, including joint angles, velocity, acceleration, and ground reaction force. The collected motion data is analyzed, and based on the analysis results, the gait model parameters are optimized to obtain the optimal gait parameters; Based on the gait model with optimal gait parameters, the initial gait pattern of the quadruped robot dog is obtained.

5. The efficient gait control method for a quadruped robot dog based on biomechanical principles according to claim 4, characterized in that, The β value is set and adjusted according to the specific hardware characteristics and task requirements of the quadruped robot dog, specifically including: Obtain the hardware characteristic parameters of the quadruped robot dog, including the joint performance, limb structure, and drive system of the quadruped robot dog; Obtain task requirement parameters, including movement speed, stability requirements, and energy consumption limits; Obtain environmental constraint parameters, including terrain complexity, ground material, and weather conditions; The β value is determined based on the hardware characteristics, task requirements, and environmental constraints of the quadruped robot dog.

6. The efficient gait control method for a quadruped robot dog based on biomechanical principles according to claim 5, characterized in that, The method also includes real-time monitoring of the robot dog's movement status and external environmental information, specifically including: Sensors, including position sensors, force sensors, vision sensors, and environmental sensors, are installed on the quadruped robot dog. Utilize sensors to perform real-time position and attitude monitoring, motion status monitoring, and external environment monitoring; Data from different sensors is fused and processed to form comprehensive monitoring information.

7. The efficient gait control method for a quadruped robot dog based on biomechanical principles according to claim 6, characterized in that, The method further includes: Based on preset alarm thresholds and comprehensive monitoring information, the robot dog's movement status and environmental parameters are monitored in real time to check for any abnormalities. When an abnormality occurs, an alarm signal is issued, and the time, location, and specific information of the abnormality are recorded.

8. A high-efficiency gait control system for a quadruped robot dog based on biomechanical principles, characterized in that, include: Gait feature acquisition and analysis module: used to collect and analyze the gait features of quadruped animals in nature, and to construct a gait model of a quadruped robot dog using biomechanical principles; Gait model simulation optimization module: Based on the gait model, the gait pattern of the quadruped robot dog is optimized through simulation technology to obtain the initial gait pattern of the quadruped robot dog; Gait pattern optimization module: Based on the gait generation algorithm and combined with the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized to obtain the final quadruped robot dog gait pattern; Gait control module: Controls the gait of the quadruped robot dog based on the final gait pattern; The gait generation algorithm uses the following calculation formula when optimizing the initial gait pattern: The E opt E represents the optimized single-step energy consumption. kin E represents the kinetic energy consumption of the robot dog in a single step. pot This represents the change in potential energy of the robot dog in a single step, where β is the potential energy influence coefficient, and T... step T represents the single-step time of the current gait. ref The single-step time is used as a reference gait.

9. A computing device, characterized in that, The device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the efficient gait control method for a quadrupedal robot dog based on biomechanical principles as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the efficient gait control method for a quadruped robot dog based on biomechanical principles as described in any one of claims 1-7.

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