Underwater quadruped robot slope terrain gait planning method and device

Abstract

The invention provides a slope terrain gait planning method and device for an underwater quadruped robot, and relates to the technical field of robot control, and the method comprises the steps: obtaining the trim angle of a robot body and a slope tilt angle, and determining the maximum trim angle of the robot on a current slope; whether the maximum trim angle is larger than or equal to the slope inclination angle or not is judged, if yes, a preset gait is adopted for climbing, and if not, the gait of the robot is dynamically adjusted; for the supporting legs, minimization of the tangential force of the front supporting legs and approaching of the propelling force of the rear supporting legs to a target value serve as optimization targets, under the condition that force and moment balance, friction cone constraint and pressure constraint are met, target foot end force of all the supporting legs is dynamically distributed, and control instructions of corresponding joints of all the supporting legs are executed; for the swinging legs, the gait cycle is prolonged according to the difference value between the slope inclination angle and the maximum trim angle, the swinging height of the front swinging leg and the falling point position of the rear swinging leg are adjusted in a self-adaptive mode, and control instructions of the joints corresponding to the swinging legs are executed.

Description

Technical Field

[0001] This invention relates to the field of robot control technology, and in particular to a method and apparatus for gait planning of an underwater quadruped robot on sloping terrain. Background Technology

[0002] Underwater quadruped robots combine the complex terrain adaptability of legged robots with the advantages of underwater operations, making them valuable for applications in seabed exploration, pipeline inspection, and rescue. However, when moving on underwater sloping terrain, especially steep inclines, the robot is affected by the righting torque generated by the combined effects of gravity and buoyancy. This forces the robot to maintain a near-horizontal posture, making it difficult to conform to the slope surface, which poses a significant challenge to traditional gait planning methods.

[0003] Current research on motion control for underwater robots mainly focuses on using thrusters to adjust attitude and position. These methods typically do not fully consider the profound impact of hydrostatics on the forces acting on the robot's support phase, its body attitude, and the contact state of its feet. When an underwater quadruped robot moves along a steep slope, the buoyancy-induced righting torque restricts its body attitude, and traditional gait planning methods cannot guarantee effective contact between the robotic legs and the slope surface. This can lead to foot slippage, instability, or a significant decrease in motion efficiency. Summary of the Invention

[0004] The purpose of this invention is to provide a gait planning method and device for underwater quadruped robots on slope terrain, in order to solve the problem mentioned in the background art that when underwater quadruped robots move on steep slopes, traditional gait planning methods cannot guarantee effective contact between the mechanical legs and the slope surface, resulting in foot slippage, instability of the robot, or a significant decrease in movement efficiency.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a gait planning method for an underwater quadruped robot on a slope, comprising the following steps: obtaining the robot's body tilt angle and slope inclination angle; determining the maximum tilt angle of the robot on the current slope based on the torque balance relationship between gravity and buoyancy acting on the robot; determining whether the maximum tilt angle is greater than or equal to the slope inclination angle; if so, adopting a preset gait for climbing; if not, dynamically adjusting the robot's gait; wherein, the dynamic adjustment of the robot's gait specifically includes: for the supporting legs, minimizing the tangential force of the front supporting leg and approaching the target value of the propulsion force of the rear supporting leg as the optimization objective; under the conditions of satisfying the balance of force and torque, friction cone constraint and pressure constraint, dynamically allocating the target foot end force of each supporting leg, and generating and executing control commands for the corresponding joints of each supporting leg; for the swinging legs, extending the gait period according to the difference between the slope inclination angle and the maximum tilt angle, adaptively adjusting the swing height of the front swinging leg and the landing position of the rear swinging leg, and generating and executing control commands for the corresponding joints of each swinging leg.

[0006] Optionally, the step of determining the maximum pitch angle of the robot on the current slope based on the torque balance relationship between the robot's gravity and buoyancy specifically includes: taking the foreleg support point as the moment center, calculating the torque generated by the robot's gravity and the torque generated by buoyancy; setting the sum of the gravity torque and the buoyancy torque to zero, the obtained fuselage pitch angle is the maximum pitch angle.

[0007] Optionally, the step of dynamically allocating the target foot force of each supporting leg specifically includes: constructing a multi-objective optimization model to minimize the tangential force of the front leg, the tangential force of the rear leg approaching the target thrust, and the normal force of the front leg approaching the target value, wherein the weight of minimizing the tangential force of the front leg > the weight of minimizing the tangential force of the rear leg approaching the target thrust > the weight of minimizing the normal force of the front leg approaching the target value; using the overall force balance, torque balance, foot friction cone constraint, and minimum normal pressure constraint of the robot as constraints for solving the multi-objective optimization model, to obtain the target foot force of each supporting leg.

[0008] Optionally, the step of generating and executing control commands for each supporting leg joint specifically includes: mapping the target foot force to the desired joint torque by transposing the Jacobian matrix of the supporting leg; and converting the desired joint torque into the corresponding joint current command and sending it to each supporting leg joint according to the pre-calibrated mapping relationship between the joint torque and the joint driving current.

[0009] Optionally, the step of extending the gait cycle based on the difference between the slope angle and the maximum pitch angle specifically includes: based on the standard gait cycle, adding an extension amount proportional to the difference between the slope angle and the maximum pitch angle to obtain the adjusted gait cycle.

[0010] Optionally, the step of adaptively adjusting the swing height of the front swing leg and the landing depth of the rear swing leg specifically includes: planning the swing leg trajectory using a parametric curve; scaling the trajectory parameters used to control the lifting height of the front leg and the trajectory parameters used to control the landing position of the rear leg proportionally according to the difference between the slope angle and the maximum longitudinal angle.

[0011] Optionally, the step of generating and executing control commands for each swing leg corresponding to the joints specifically includes: obtaining the target angle of each joint of the swing leg through inverse kinematics calculation based on the adjusted swing trajectory; and issuing the target angle as a control command to each swing leg corresponding to the joint.

[0012] On the other hand, the present invention also provides an underwater quadruped robot gait planning device for slope terrain, comprising: an acquisition module for acquiring the robot's body tilt angle and slope inclination angle, and determining the robot's maximum tilt angle on the current slope based on the torque balance relationship between gravity and buoyancy acting on the robot; and a judgment module for judging whether the maximum tilt angle is greater than or equal to the slope inclination angle. If so, a preset gait is used for climbing the slope; otherwise, the robot's gait is dynamically adjusted. The dynamic adjustment of the robot's gait specifically includes: a support leg control module. For the supporting leg, the optimization goal is to minimize the tangential force of the front supporting leg and make the propulsive force of the rear supporting leg approach the target value. Under the conditions of satisfying the balance of force and torque, friction cone constraint and pressure constraint, the target foot force of each supporting leg is dynamically allocated, and control commands for the corresponding joints of each supporting leg are generated and executed. The swing leg control module is used to extend the gait period according to the difference between the slope angle and the maximum longitudinal tilt angle, adaptively adjust the swing height of the front swing leg and the landing position of the rear swing leg, and generate and execute control commands for the corresponding joints of each swing leg.

[0013] On the other hand, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the underwater quadruped robot slope terrain gait planning method described above.

[0014] On the other hand, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the underwater quadruped robot gait planning method for slope terrain described above.

[0015] Compared with the prior art, the beneficial effects of the present invention are: This application introduces a maximum pitch angle prediction mechanism based on the balance of gravity and buoyancy torque, enabling the underwater quadruped robot to intelligently identify attitude adjustment limits and actively switch to dynamic adjustment mode when the limits are exceeded. This mode co-optimizes the force distribution at the foot end of the supporting leg and the trajectory planning of the swing leg. On the one hand, the mechanical strategy of reducing the load on the front leg and focusing on propulsion on the hind leg ensures that the foot end can still obtain reliable slope contact and traction under restricted posture, effectively suppressing slippage and instability caused by righting torque in the underwater environment. On the other hand, by adaptively adjusting the gait cycle and the position of the leg lift, the robot's overall adaptability and motion robustness to different slope terrains are enhanced, thereby achieving stable and reliable crawling on steep slopes. Attached Figure Description

[0016] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0017] Figure 2This is a schematic diagram of the crawling ramp control architecture of the present invention.

[0018] Figure 3 This is a schematic diagram of the system structure of the present invention.

[0019] In the diagram: 10 - Acquisition module, 20 - Judgment module, 30 - Support leg control module, 40 - Swing leg control module. Detailed Implementation

[0020] The present invention will now be clearly and completely described in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0021] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be used interchangeably where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0022] Those skilled in the art will understand that, unless explicitly stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in the specification of this application means the presence of features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0023] It will be understood by those skilled in the art that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0024] It should be understood that the sequence number and size of each step in this embodiment do not imply the order of execution. The execution order of each process is determined by its function and internal logic, and should not constitute any limitation on the implementation process of this application embodiment.

[0025] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. This application will now be described in detail with reference to the accompanying drawings and embodiments.

[0026] Please refer to Figures 1-2 This invention discloses a gait planning method for an underwater quadruped robot on a slope, comprising the following steps: acquiring the robot's body tilt angle and slope inclination angle; determining the maximum tilt angle of the robot on the current slope based on the torque balance relationship between gravity and buoyancy; determining whether the maximum tilt angle is greater than or equal to the slope inclination angle; if so, adopting a preset gait for climbing; otherwise, dynamically adjusting the robot's gait; wherein, the dynamic adjustment of the robot's gait specifically includes: for the supporting legs, minimizing the tangential force of the front supporting leg and approaching the target value of the propulsion force of the rear supporting leg as the optimization goal; under the conditions of satisfying force and torque balance, friction cone constraint, and pressure constraint, dynamically allocating the target foot end force of each supporting leg, and generating and executing control commands for the corresponding joints of each supporting leg; for the swinging legs, extending the gait period according to the difference between the slope inclination angle and the maximum tilt angle, adaptively adjusting the swing height of the front swinging leg and the landing position of the rear swinging leg, and generating and executing control commands for the corresponding joints of each swinging leg.

[0027] Specifically, the robot's current tilt angle θ and the slope angle θ_s are obtained using IMU sensors and depth gauges. Based on the torque balance relationship between gravity and buoyancy acting on the robot, the maximum tilt angle θ_max that it can achieve on the current slope is calculated. A decision is made by comparing the slope angle θ_s with the maximum tilt angle θ_max: if θ_s ≤ θ_max, it means that the robot is capable of adjusting its body posture to fully conform to the slope, and therefore adopts a preset standard gait for climbing; if θ_s > θ_max, it means that due to the underwater righting torque, the robot's body cannot reach the slope angle, and the gait must be dynamically adjusted.

[0028] The dynamic adjustment is specifically divided into the coordinated optimization of the supporting legs and the swinging legs. For the legs in the supporting phase, the core of the adjustment lies in the redistribution of foot force. The optimization goal is to minimize the tangential force provided by the front supporting leg while making the propulsive force provided by the rear supporting leg approach a preset target value. This optimization process must strictly meet the force and torque balance of the robot as a whole, the friction cone constraint of the foot contacting the slope, and the minimum pressure constraint required to maintain contact. Finally, the target foot force of each supporting leg is dynamically calculated, and joint control commands are generated accordingly. For the legs in the swinging phase, the adjustment focuses on trajectory and timing. First, the gait period is extended according to the slope difference to allow more time for adjustment. At the same time, the ground clearance of the front swinging leg is adaptively increased to avoid interference with the slope, and the landing position of the rear swinging leg is adjusted to ensure effective contact. Finally, corresponding joint control commands are generated based on the planned new trajectory. Through the above synchronous and targeted adjustment of the supporting legs and the swinging legs, stable and reliable crawling under hydrostatic constraints on steep slopes is achieved.

[0029] This application introduces a maximum pitch angle prediction mechanism based on the balance of gravity and buoyancy torque, enabling the underwater quadruped robot to intelligently identify attitude adjustment limits and actively switch to dynamic adjustment mode when the limits are exceeded. This mode co-optimizes the force distribution at the foot end of the supporting leg and the trajectory planning of the swing leg. On the one hand, the mechanical strategy of reducing the load on the front leg and focusing on propulsion on the hind leg ensures that the foot end can still obtain reliable slope contact and traction under restricted posture, effectively suppressing slippage and instability caused by righting torque in the underwater environment. On the other hand, by adaptively adjusting the gait cycle and the position of the leg lift, the robot's overall adaptability and motion robustness to different slope terrains are enhanced, thereby achieving stable and reliable crawling on steep slopes.

[0030] In some embodiments, the step of determining the maximum pitch angle of the robot on the current slope based on the torque balance relationship between the gravity and buoyancy acting on the robot specifically includes: taking the foreleg support point as the moment center, calculating the torque generated by the robot's gravity and the torque generated by buoyancy; setting the sum of the gravity torque and the buoyancy torque to zero, the obtained fuselage pitch angle is the maximum pitch angle.

[0031] Specifically, a mechanical model is established with the robot's front leg support point as the moment center. Under this model, the moment M_g of the robot's gravity relative to the support point is calculated, and its magnitude is related to the position of the robot's center of gravity; at the same time, the moment M_b of the buoyancy F_b relative to the same support point is calculated, and its magnitude is related to the position of the center of buoyancy.

[0032] The gravitational torque M_g can be expressed as M_g=mg*(z_f*sinθ+x_f*cosθ), and the buoyancy torque M_b can be expressed as M_b=F_b[(z_b-z_f)sinθ+(x_b-x_f)cosθ], where (x_b,z_b) are the coordinates of the center of buoyancy, (x_f,z_f) are the coordinates of the front leg support point, and m is the mass of the robot.

[0033] According to static equilibrium, let the sum of the gravitational torque and the buoyancy torque be zero, i.e., M_g + M_b = 0. By solving this equation, we can obtain the maximum pitch angle θ_max that the robot can maintain balance. Its specific expression is tanθ_max = -[x_f + α(x_b - x_f)] / [z_f + α(z_b - z_f)], where α = F_b / (mg) is the buoyancy ratio, θ is the robot's pitch angle, and θ_max is the limit pitch angle that the body can reach during the front leg support phase on the current slope.

[0034] This application establishes a torque balance model with the foreleg support point as the center of torque, and solves the equation that the sum of the gravitational torque and the buoyancy torque is zero to determine the maximum pitch angle. This enables the robot to calculate the theoretical posture boundary on the current slope in real time based on its own mass, buoyancy and the position of the center of buoyancy, providing a reliable and quantitative decision basis for the intelligent switching of subsequent gait modes and avoiding misjudgments caused by experience or rough estimation.

[0035] In some embodiments, the step of dynamically allocating the target foot force of each supporting leg specifically includes: constructing a multi-objective optimization model to minimize the tangential force of the front leg, the tangential force of the rear leg approaching the target thrust, and the normal force of the front leg approaching the target value, wherein the weight of minimizing the tangential force of the front leg > the weight of minimizing the tangential force of the rear leg approaching the target thrust > the weight of minimizing the normal force of the front leg approaching the target value; using the overall force balance, torque balance, foot friction cone constraint, and minimum normal pressure constraint of the robot as constraints for solving the multi-objective optimization model, to obtain the target foot force of each supporting leg.

[0036] Specifically, when the robot is climbing a slope with a diagonal gait and in a dual-support phase, such as with the right front leg and the left rear leg supporting the weight, it is necessary to optimize the distribution of foot force between the front and rear supporting legs. First, a multi-objective optimization function needs to be established. .

[0037] The function consists of a weighted sum of three terms: the first term The purpose is to punish the tangential force of the forelegs. This will cause it to be minimized; the second term The aim is to encourage tangential force in the hind legs. Propulsion towards expectation ; Third item Allowing for front leg normal force It varies slightly around a reasonable nominal value.

[0038] The design of the weights follows > > The principle The value is 0.5-0.9, used to punish the tangential force on the forelegs and make the forelegs mainly bear the normal force; A value of 0.4-0.6 is used to encourage the hind legs to provide propulsion close to the desired value; It is 0.1-0.4, which is used to allow the normal force of the front leg to vary within a certain range.

[0039] Solving this optimization problem requires addressing multiple constraints. The force balance constraint equations for the robot on the slope's normal, tangential, and lateral directions are as follows: Normal balance. Tangential balance Lateral balance ;in, =Ct×½P×V 2 ×S represents the water resistance, flowing down the slope. The overall moment balance constraint equation, with the center of moment P as the support point of the foreleg, is as follows: ,in, Let P be the position vector of the hind leg contact point relative to P. The direction of gravity. And the friction cone constraint of the forces at the foot ends of each supporting leg: ; The constraint that the normal pressure must be greater than a minimum threshold is applied. ; By solving this constrained optimization problem, the optimized target foot-end forces F_f and F_h of the front and rear support legs can be obtained.

[0040] This application constructs a multi-objective optimization model with specific weight priorities, minimizing the weight of the foreleg tangential force being greater than the weight of the hindleg thrust tracking force being greater than the weight of the foreleg normal force maintenance force, thus achieving a scientific and precise allocation of the foot-end force of the supporting leg. It forces the optimization process to prioritize unloading the tangential load from the foreleg, thereby concentrating its normal force resources on maintaining contact; simultaneously, it drives the hind leg to provide a near-desired main thrust force. This force allocation strategy effectively coordinates the functional division of labor between the fore and hind legs, maximizing the utilization of limited plantar friction while satisfying overall mechanical balance and contact constraints, fundamentally suppressing the potential slippage tendency of both fore and hind legs.

[0041] In some embodiments, the step of generating and executing control commands for each supporting leg joint specifically includes: mapping the target foot force to a desired joint torque by transposing the Jacobian matrix of the supporting leg; converting the desired joint torque into a corresponding joint current command and sending it to each supporting leg joint according to a pre-calibrated mapping relationship between the joint torque and the joint drive current.

[0042] Specifically, for each supporting leg, given its expected foot force vector F_d containing Fx, Fy, and Fz, the Jacobian matrix J, which describes the relationship between joint velocity and foot velocity in the current configuration, is used to transpose the vector. It can map foot forces to joint space and calculate the desired joint torque. Since underwater joints are typically driven by motors and involve transmission mechanisms and fluid damping, directly controlling the torque can be complex. Therefore, this application calibrates the static or dynamic mapping relationship between the joint drive current I and the output torque τ through pre-conducted underwater joint motion tests. After obtaining the desired joint torque τ_d, the corresponding joint current command can be calculated based on this mapping relationship and sent to the actuator of the corresponding joint, thereby achieving precise force control of the supporting leg joint and enabling it to output the required foot force.

[0043] This application maps the optimized foot force to joint torque by transposing the Jacobian matrix, and further uses the pre-calibrated torque-current relationship to convert it into drive commands, forming a complete and precise control link from high-level algorithm decision-making to low-level physical execution. This effectively and reliably transmits and implements the model-based foot force optimization results into the actual output of the joint motor, ensuring that the support leg can accurately generate the required ground reaction force. It is particularly suitable for underwater joint actuators with nonlinear friction and fluid damping.

[0044] In some embodiments, the step of extending the gait cycle based on the difference between the slope angle and the maximum pitch angle specifically includes: based on the standard gait cycle, adding an extension amount proportional to the difference between the slope angle and the maximum pitch angle to obtain an adjusted gait cycle.

[0045] Specifically, when a dynamic adjustment mode is required, the standard gait cycle T is no longer applicable because more complex trajectory and force adjustments require more time to complete. The adjusted gait cycle is then requested. The slope difference Δθ = θ_s - θ_max is linearly extended. The specific calculation formula is as follows: ,in, For standard gait cycles, Δθ is a pre-set normal adjustment coefficient. The larger the Δθ, the more challenging the terrain, and the greater the adjustment range may be required, thus resulting in a longer gait cycle. This cycle extension strategy provides the swing leg with more time to complete a higher leg lift or a more cautious leg landing, while also making the force control process of the stance phase smoother.

[0046] This application linearly extends the gait cycle based on the difference between the slope angle and the maximum pitch angle, providing the necessary time resources for dynamic adjustment modes. The cycle extension is proportional to the terrain difficulty, allowing the robot more time to complete more complex processes such as leg lifting for obstacle avoidance, careful footing, and force adjustment of the supporting leg when facing more challenging slopes. This avoids problems such as incomplete movements, large trajectory tracking errors, or sudden changes in force control caused by time constraints, thereby ensuring the stability and controllability of the entire gait adjustment.

[0047] In some embodiments, the step of adaptively adjusting the swing height of the front swing leg and the landing depth of the rear swing leg specifically includes: planning the swing leg trajectory using a parametric curve; scaling the trajectory parameters for controlling the lifting height of the front leg and the trajectory parameters for controlling the landing position of the rear leg proportionally according to the difference between the slope angle and the maximum longitudinal angle.

[0048] Specifically, the swing leg trajectory is planned using parametric curves, such as cubic Bézier curves, whose shape is determined by a series of control points: In the formula: The hind legs are off the ground; Moving downwards; Ready to make contact; The target landing point for the hind leg. For the front swing leg, its trajectory is designed to avoid collision with the slope and land smoothly.

[0049] During adjustment, the key control point parameters for controlling the leg lift height are proportionally enlarged based on the slope difference Δθ. (Base leg lift height) Multiply by a gain factor related to Δθ The adjusted height parameters are obtained. For the back swing leg, its trajectory needs to consider downward movement to contact a potentially lower target landing point. Similarly, the control point parameters controlling the initial descent depth and the height of the preparation contact phase are scaled according to Δθ, with a base height... Multiply by gain factor In addition, the planned entire trajectory It also needs to meet obstacle avoidance constraints, that is, its Z coordinate must always be greater than the height of the corresponding point on the slope surface. , Safety margin This safety margin is related to speed. It can also adaptively adjust based on the velocity of the trajectory points to ensure absolutely no collisions.

[0050] This application employs parametric curve planning of the trajectory and scales key height and position parameters proportionally based on the slope difference, enabling flexible and adaptive adjustment of the swing leg trajectory. This allows the lifting height of the front leg and the landing depth of the rear leg to be automatically adjusted according to the terrain challenge. The former effectively avoids accidental collisions between the feet and the slope due to the limited attitude of the aircraft, while the latter ensures that the feet can still contact the slope in a suitable attitude and position when the aircraft is tilted, laying the foundation for establishing stable support.

[0051] In some embodiments, the step of generating and executing control commands for each swing leg corresponding to a joint specifically includes: obtaining the target angle of each joint of the swing leg through inverse kinematics calculation based on the adjusted swing trajectory; and issuing the target angle as a control command to each joint of the swing leg corresponding to a joint.

[0052] Specifically, after obtaining the adjusted foot swing trajectory, it needs to be converted into angle commands for each joint. For a leg structure with three rotational degrees of freedom, such as hip inversion / extension θ1, thigh pitch θ2, and lower leg pitch θ3, this conversion can be achieved through inverse kinematics. Given the target foot position and the coordinates of the hip joint mounting point. Given the thigh length L1 and the calf length L2, the corresponding joint angles can be calculated.

[0053] Define local coordinates: The formula for calculating the joint angle is: ; Arctan2(y, x) is the arctangent function in the four quadrants, which returns the argument of y / x. These target angle values ​​are used as position commands and sent directly to the actuators of each joint, so that the swing leg can accurately follow the planned trajectory to complete the lifting, swinging and lowering movements.

[0054] This application performs inverse kinematics calculations based on the adjusted trajectory and directly issues joint angle commands, realizing the precise and efficient conversion of the swing leg from the spatial trajectory at the foot end to the spatial motion of the joint. It ensures that the planned obstacle avoidance and foot landing trajectory can be accurately reproduced by the mechanical leg. The direct control of the joint angle is fast and easy to implement, effectively guaranteeing the accuracy and reliability of the swing leg movement.

[0055] Please refer to Figure 3On the other hand, the present invention also provides an underwater quadruped robot gait planning device for slope terrain, comprising: an acquisition module 10, used to acquire the robot's body tilt angle and slope inclination angle, and determine the maximum tilt angle of the robot on the current slope based on the torque balance relationship between gravity and buoyancy acting on the robot; and a judgment module 20, used to determine whether the maximum tilt angle is greater than or equal to the slope inclination angle, and if so, to use a preset gait for climbing the slope, and if not, to dynamically adjust the robot's gait; wherein, the dynamic adjustment of the robot's gait specifically includes: a support leg control module. Block 30 is used to optimize the tangential force of the front support leg and the propulsive force of the rear support leg to approach the target value for the support leg. Under the conditions of force and torque balance, friction cone constraint and pressure constraint, it dynamically allocates the target foot end force of each support leg and generates and executes the control commands of the corresponding joints of each support leg. The swing leg control module 40 is used to extend the gait period according to the difference between the slope angle and the maximum longitudinal tilt angle, adaptively adjust the swing height of the front swing leg and the landing position of the rear swing leg, and generate and execute the control commands of the corresponding joints of each swing leg for the swing leg.

[0056] On the other hand, the present invention also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the underwater quadruped robot slope terrain gait planning method described above.

[0057] On the other hand, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the underwater quadruped robot gait planning method for slope terrain described above.

[0058] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause an electronic device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0059] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, database, or other media used in the embodiments provided by this invention can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0060] The above are merely embodiments of the present invention and do not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention's specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for gait planning of an underwater quadruped robot on sloping terrain, characterized by the following steps: include: Obtain the robot's tilt angle and slope angle, and determine the robot's maximum tilt angle on the current slope based on the torque balance relationship between gravity and buoyancy. Determine whether the maximum pitch angle is greater than or equal to the slope angle. If yes, then use a preset gait to climb the slope. If no, then dynamically adjust the robot's gait. Specifically, the dynamic adjustment of the robot's gait includes: For the supporting legs, the optimization objectives are to minimize the tangential force of the front supporting legs and to make the propulsion force of the rear supporting legs approach the target value. Under the conditions of satisfying the balance of force and torque, friction cone constraint and pressure constraint, the target foot end force of each supporting leg is dynamically allocated, and control commands for the corresponding joints of each supporting leg are generated and executed. For the swing leg, the gait cycle is extended according to the difference between the slope angle and the maximum longitudinal tilt angle, the swing height of the front swing leg and the landing position of the rear swing leg are adaptively adjusted, and control commands for the corresponding joints of each swing leg are generated and executed.

2. The underwater quadruped robot gait planning method for slope terrain according to claim 1, characterized in that, The step of determining the robot's maximum pitch angle on the current slope based on the torque balance relationship between gravity and buoyancy on the robot specifically includes: Using the foreleg support point as the center of moment, calculate the torque generated by the robot's gravity and the torque generated by buoyancy. Setting the sum of the gravitational torque and the buoyancy torque to zero, the calculated fuselage pitch angle is the maximum pitch angle.

3. The underwater quadruped robot gait planning method for slope terrain according to claim 1, characterized in that, The specific steps of dynamically allocating the target foot force of each supporting leg include: A multi-objective optimization model is constructed to minimize the tangential force of the forelegs, the tangential force of the hindlegs approaching the target thrust, and the normal force of the forelegs approaching the target value. Among them, the weight of minimizing the tangential force of the forelegs is greater than that of minimizing the tangential force of the hindlegs approaching the target thrust, which is greater than that of minimizing the normal force of the forelegs approaching the target value. The target foot force of each supporting leg is obtained by using the overall force balance, torque balance, foot friction cone constraint, and minimum normal pressure constraint of the robot as the constraint conditions for solving the multi-objective optimization model.

4. The underwater quadruped robot gait planning method for slope terrain according to claim 3, characterized in that, The step of generating and executing control commands for the corresponding joints of each supporting leg specifically includes: The target foot force is mapped to the desired joint torque by transposing the Jacobian matrix of the supporting leg; Based on the pre-calibrated mapping relationship between joint torque and joint drive current, the desired joint torque is converted into a corresponding joint current command and sent to the corresponding joint of each supporting leg.

5. The underwater quadruped robot gait planning method for slope terrain according to claim 1, characterized in that, The step of extending the gait period based on the difference between the slope angle and the maximum longitudinal tilt angle specifically includes: Based on the standard gait cycle, an extension proportional to the difference between the slope angle and the maximum pitch angle is added to obtain the adjusted gait cycle.

6. The underwater quadruped robot gait planning method for slope terrain according to claim 5, characterized in that, The steps for adaptively adjusting the swing height of the front swing leg and the landing depth of the rear swing leg specifically include: Parametric curves are used to plan the trajectory of the swing leg; Based on the difference between the slope angle and the maximum longitudinal angle, the trajectory parameters for controlling the lifting height of the front leg and the trajectory parameters for controlling the landing position of the hind leg are scaled proportionally.

7. The underwater quadruped robot gait planning method for slope terrain according to claim 6, characterized in that, The steps of generating and executing control commands for each swing leg's corresponding joints specifically include: Based on the adjusted swing trajectory, the target angles of each joint of the swing leg are obtained through inverse kinematics calculation. The target angle is sent as a control command to the corresponding joints of each swinging leg.

8. A gait planning device for an underwater quadruped robot on slope terrain, characterized in that, include: The acquisition module is used to acquire the robot's body tilt angle and slope tilt angle, and determine the robot's maximum tilt angle on the current slope based on the torque balance relationship between the robot's gravity and buoyancy. The judgment module is used to determine whether the maximum pitch angle is greater than or equal to the slope angle. If so, the robot will climb the slope using a preset gait; otherwise, the robot's gait will be dynamically adjusted. Specifically, the dynamic adjustment of the robot's gait includes: The support leg control module is used to optimize the support leg by minimizing the tangential force of the front support leg and bringing the thrust of the rear support leg close to the target value. Under the conditions of satisfying the balance of force and torque, friction cone constraint and pressure constraint, it dynamically allocates the target foot end force of each support leg and generates and executes the control commands of the corresponding joints of each support leg. The swing leg control module is used to extend the gait cycle based on the difference between the slope angle and the maximum longitudinal tilt angle, adaptively adjust the swing height of the front swing leg and the landing position of the rear swing leg, and generate and execute control commands for the corresponding joints of each swing leg.

9. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the underwater quadruped robot gait planning method for slope terrain as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the underwater quadruped robot gait planning method for slope terrain as described in any one of claims 1 to 7.

Images