Efficient gait control method for quadruped robot dog based on biomechanical principle

Abstract

The invention discloses a biomechanical principle-based efficient gait control method for a quadruped robot dog, which can provide a more real reference for the design of the quadruped robot dog by collecting and analyzing the gait characteristics of the quadruped animal in the nature, so that the gait of the quadruped robot dog is closer to the nature, the walking fluency and stability are improved, and the safety of the quadruped robot dog is improved. A simulation technology is used for optimizing a gait model, an efficient and energy-saving gait mode can be obtained, energy consumption is reduced, the walking speed and efficiency are improved, meanwhile, hardware characteristics of the four-footed robot dog are considered, an initial gait mode is optimized through a gait generation algorithm, the four-footed robot dog is made to adapt to different physical structures and movement capacities, stable walking in a complex environment is kept, and the walking efficiency is improved. And by applying a specific calculation formula and adjusting algorithm parameters, the single-step energy consumption can be remarkably reduced, the overall energy efficiency is improved, multiple motion modes are generated to adapt to different environment and task requirements, the walking efficiency of the robot dog is effectively improved, and unnecessary energy consumption and actions are reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of gait control of a quadruped robot dog, and in particular to an efficient gait control method for a quadruped robot dog based on biomechanical principles. Background Art

[0002] As an important branch of modern robotics technology, the motion control and gait optimization of quadruped robot dogs have always been a hot topic and difficulty in the research field. Traditional gait control methods for quadruped robot dogs are mostly based on preset gait patterns and fixed control strategies. These methods often show great limitations when dealing with complex and 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 mission requirements. These gait patterns not only possess efficient and stable locomotion but also adapt to varying environmental and mission conditions. Therefore, drawing on the gait characteristics of natural quadrupeds can provide valuable inspiration and reference for gait control in quadruped robot dogs. Summary of the Invention

[0004] In view of this, the present invention proposes an efficient gait control method for a quadruped robot dog based on biomechanical principles, which can effectively solve the defects of the existing technology in coping with complex and changing environments and task requirements.

[0005] The technical solution of the present invention is achieved as follows:

[0006] An efficient gait control method for a quadruped robot dog based on biomechanical principles, comprising:

[0007] Collect and analyze the gait characteristics of quadrupeds in nature, and use biomechanical principles to build a gait model for a quadruped robot dog;

[0008] Based on the gait model, the gait pattern of the quadruped robot dog is optimized by simulation technology to obtain an 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] performing gait control on the quadruped robot dog according to the final gait pattern of the quadruped robot dog;

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

[0012]

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

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

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

[0016] extracting gait features from the gait data, wherein the gait features include joint angle changes and limb movement trajectories within a gait cycle;

[0017] Performing statistical analysis on the extracted gait features to obtain relationships between the gait features and the animal's motor performance, including relationships between gait frequency and speed, and between step length and stability;

[0018] Based on the principles of biomechanics and combined with the analysis results of the gait characteristics of quadrupeds, a gait model of a quadruped robot dog is constructed.

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

[0020] Using the principles of kinematics and the analysis of quadruped gait characteristics, the kinematic relationships between the joints of the quadruped robot dog are established, including forward kinematics and inverse kinematics.

[0021] Based on the analysis results of dynamic principles and quadruped gait characteristics, the force conditions of the quadruped robot dog during movement are analyzed and the dynamic equation is established;

[0022] The kinematic model and the dynamic model are integrated to obtain the gait model of the quadruped robot dog.

[0023] As a further optional solution to the efficient gait control method for a quadruped robot dog based on biomechanical principles, the method of optimizing the gait pattern of the quadruped robot dog by 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 a quadruped robot dog in the simulation tool and set the simulation environment parameters;

[0025] Importing the gait model into a simulation environment, and 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, velocities, accelerations, and ground reaction forces.

[0027] Analyze the collected motion data and optimize the parameters of the gait model based on the analysis results to obtain the optimal gait parameters;

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

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

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

[0031] Obtaining task requirement parameters, wherein the task requirement parameters include motion speed, stability requirements, and energy consumption limits;

[0032] Obtaining environmental constraint parameters, wherein the environmental constraint parameters include terrain complexity, ground material, and weather conditions;

[0033] The β value is determined based on the hardware characteristic parameters, task requirement parameters and environmental constraint parameters of the quadruped robot dog.

[0034] As a further optional solution to the 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 environment information, specifically including:

[0035] Install sensors on the quadruped robot dog, including position sensors, force sensors, vision sensors, and environmental sensors;

[0036] Use sensors to monitor position and posture, motion status, and external environment in real time;

[0037] The data from different sensors are integrated and processed to form comprehensive monitoring information.

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

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

[0040] An efficient gait control system for a quadruped robot dog based on biomechanical principles, comprising:

[0041] Gait feature acquisition and analysis module: used to collect and analyze the gait characteristics of quadrupeds in nature and build a gait model for a quadruped robot dog using biomechanical principles;

[0042] Gait model simulation and optimization module: based on the gait model, the gait pattern of the quadruped robot dog is optimized by 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 the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized to obtain the final gait pattern of the quadruped robot dog;

[0044] Gait control module: controls the gait of the quadruped robot dog according to the final gait pattern of the quadruped robot dog;

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

[0046]

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

[0048] A computing device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the processor implements any one of the steps of the above-mentioned method for efficiently controlling the gait of a quadruped robot dog based on biomechanical principles.

[0049] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the computer program implements the steps of any one of the above-mentioned methods for efficiently controlling the gait of a quadruped robot dog based on biomechanical principles.

[0050] The beneficial effects of the present invention are as follows: by collecting and analyzing the gait characteristics of quadrupeds in nature, the walking style of quadrupeds can be simulated more accurately, providing a more realistic reference for the design of a quadruped robot dog, making the gait of the quadruped robot dog closer to nature, thereby improving the smoothness and stability of its walking. By optimizing the gait model using simulation technology, a more efficient and energy-saving gait pattern can be obtained. The optimized gait pattern can reduce the energy consumption of the quadruped robot dog during walking, while improving its walking speed and efficiency. In addition, by considering the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized through the gait generation algorithm, so that the final gait pattern can better adapt to the quadruped robot The physical structure and movement ability of the robot dog, this highly adaptable gait pattern enables the four-legged robot dog to maintain stable walking in various complex environments. In addition, a specific calculation formula is applied to optimize the initial gait pattern. The optimized gait pattern can significantly reduce the single-step energy consumption of the robot dog during walking, thereby improving its overall energy efficiency. By adjusting the parameters in the gait generation algorithm, this technical solution can enable the robot dog to adapt to different walking environments and task requirements. It not only optimizes the energy consumption of a single gait, but also can generate a variety of different movement patterns by adjusting the algorithm parameters. By optimizing the gait pattern, this technical solution can improve the walking efficiency of the robot dog and reduce unnecessary energy consumption and movements. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 1 This is a flow chart of 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 an efficient gait control system for a quadruped robot dog based on biomechanical principles of the present invention;

[0054] Figure 3 A schematic diagram of the composition of a computing device according to the present invention. DETAILED DESCRIPTION

[0055] The following is a clear and complete description of the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

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

[0057] Collect and analyze the gait characteristics of quadrupeds in nature, and use biomechanical principles to build a gait model for a quadruped robot dog;

[0058] Based on the gait model, the gait pattern of the quadruped robot dog is optimized by simulation technology to obtain an 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] performing gait control on the quadruped robot dog according to the final gait pattern of the quadruped robot dog;

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

[0062]

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

[0064] In this embodiment, by collecting and analyzing the gait characteristics of quadrupeds in nature, the walking style of quadrupeds can be simulated more accurately, providing a more realistic reference for the design of a quadruped robot dog, making the gait of the quadruped robot dog closer to nature, thereby improving the smoothness and stability of its walking. By optimizing the gait model using simulation technology, a more efficient and energy-saving gait pattern can be obtained. The optimized gait pattern can reduce the energy consumption of the quadruped robot dog during walking, while improving its walking speed and efficiency. In addition, by considering the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized through the gait generation algorithm, so that the final gait pattern can better adapt to the quadruped robot dog. The physical structure and movement ability of the robot are such that this highly adaptable gait pattern enables the quadruped robot dog to maintain stable walking in various complex environments. In addition, a specific calculation formula is applied to optimize the initial gait pattern. The optimized gait pattern can significantly reduce the energy consumption of a single step of the robot dog during walking, thereby improving its overall energy efficiency. By adjusting the parameters in the gait generation algorithm, this technical solution can enable 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 can generate a variety of different movement patterns by adjusting the algorithm parameters. By optimizing the gait pattern, this technical solution can improve the walking efficiency of the robot dog and reduce unnecessary energy consumption and movements.

[0065] It should be noted that through the hardware characteristics of the quadruped robot dog, it is possible to analyze the energy changes in the initial gait pattern of the quadruped robot dog, and analyze and adjust the energy changes through the gait generation algorithm, so as to obtain the gait pattern with the lowest energy consumption that the quadruped robot dog can maintain stable walking in various complex environments.

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

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

[0068] extracting gait features from the gait data, wherein the gait features include joint angle changes and limb movement trajectories within a gait cycle;

[0069] Performing statistical analysis on the extracted gait features to obtain relationships between the gait features and the animal's motor performance, including relationships between gait frequency and speed, and between step length and stability;

[0070] Based on the principles of biomechanics and combined with the analysis results of the gait characteristics of quadrupeds, a gait model of a quadruped robot dog is constructed.

[0071] In this embodiment, by acquiring the gait data of quadrupeds under different terrains, speeds and task conditions, we can fully understand the walking characteristics of quadrupeds in different environments. The comprehensiveness of the data helps to build a more accurate and adaptable gait model of a quadruped robot dog; the gait features extracted from the gait data, such as joint angle changes and limb movement trajectories, are key information for building a gait model. Accurately extracting these features can ensure that the gait model is highly consistent with the actual walking method of the quadruped, thereby improving the effectiveness of the model; statistical analysis is performed on the extracted gait features to obtain the relationship between the gait features and the animal's movement performance, such as step frequency and speed, step length and stability, etc. It helps to reasonably set the gait parameters according to the actual needs of the quadruped robot dog when constructing the gait model to achieve the best walking effect; combining the principles of biomechanics, analyzing the gait characteristics of quadrupeds can reveal the mechanical mechanism and energy conversion law during their walking process, which helps to simulate a more realistic and efficient walking method when constructing the gait model of the quadruped robot dog, and improve the walking efficiency and stability of the robot dog; the gait model constructed based on the principles of biomechanics and the analysis results of the gait characteristics of quadrupeds has high practicality and reliability. This model can guide the walking strategies of the quadruped robot dog in different environments, enabling it to adapt to various complex terrains and task requirements.

[0072] Preferably, the gait model of the quadruped robot dog is constructed based on the biomechanical principles and the analysis results of the gait characteristics of quadrupeds, specifically including:

[0073] Using the principles of kinematics and the analysis of quadruped gait characteristics, the kinematic relationships between the joints of the quadruped robot dog are established, including forward kinematics and inverse kinematics.

[0074] Based on the analysis results of dynamic principles and quadruped gait characteristics, the force conditions of the quadruped robot dog during movement are analyzed and the dynamic equation is established;

[0075] The kinematic model and the dynamic model are integrated to obtain the gait model of the quadruped robot dog.

[0076] In this embodiment, by utilizing the analysis results of kinematic principles and quadruped gait characteristics, the technical solution can accurately establish the motion relationship between the joints of the quadruped robot dog, which includes forward kinematics (calculating the position and direction of the end effector based on the joint angle) and inverse kinematics (calculating the joint angle based on the position and direction of the end effector). The precise motion relationship helps to ensure the coordinated movement of the joints of the quadruped robot dog during walking, thereby improving the stability and efficiency of walking; based on the analysis results of dynamic principles and quadruped gait characteristics, the technical solution can deeply analyze the force conditions of the quadruped robot dog during movement, including gravity, ground reaction force, inertia force, etc., and how these forces affect the motion state and gait of the quadruped robot dog. By establishing dynamic equations, the quadruped robot can be predicted and controlled more accurately. The movement behavior of the robot dog is optimized, thereby improving the accuracy and adaptability of its walking; the kinematic model and the dynamic model are integrated to obtain the gait model of the quadruped robot dog. This integration not only takes into account the movement relationship between the joints of the quadruped robot dog, but also takes into account the force conditions during the movement. By optimizing the gait model, the walking performance of the quadruped robot dog can be further improved, including increasing walking speed, reducing energy consumption, and enhancing stability. This technical solution not only provides a scientific gait model for the quadruped robot dog, but also provides a basis for its intelligent control. By combining the gait model with hardware such as sensors and controllers, the quadruped robot dog's autonomous navigation, obstacle avoidance, path planning and other functions can be realized, which helps to improve the intelligence level and autonomous ability of the quadruped robot dog, 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 from joint angles to the position and posture of the end effector (foot). In a quadruped robot dog, forward kinematics can be used to calculate the position and posture of the foot in space given the joint angles. This involves the geometric relationship between parameters such as link length and joint angle, and can be achieved through kinematic modeling methods such as the DH parameter method, Lie algebra method, or screw theory.

[0079] Inverse kinematics: Inverse kinematics is the process of inferring the desired angles of each joint from the target position and posture of the end effector (foot). In quadruped robot dogs, inverse kinematics is used to plan the foot's trajectory and calculate the joint angles required to achieve that trajectory.

[0080] The kinetic model establishment includes:

[0081] Force analysis: Based on the principles of dynamics, the forces acting on the quadruped robot during its movement are analyzed, including gravity, ground reaction force, inertia, etc. The effects of factors such as the quadruped robot's mass distribution, joint stiffness, and ground conditions on the force need to be considered.

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

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

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

[0085] Importing the gait model into a simulation environment, and 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, velocities, accelerations, and ground reaction forces.

[0087] Analyze the collected motion data and optimize the parameters of the gait model based on the analysis results to obtain the optimal gait parameters;

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

[0089] In this embodiment, the virtual model of the quadruped robot dog built in the simulation tool can highly restore its real physical characteristics and movement mechanism. The set simulation environment parameters, such as terrain, friction, gravity, etc., can simulate a variety of actual walking scenarios, providing a rich test environment for the optimization of gait patterns. The gait model is imported into the simulation environment, and the quadruped robot dog is allowed 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, speeds, accelerations, ground reaction forces, etc., the performance of the gait model can be comprehensively evaluated. The parameters of the gait model are optimized based on the analysis results, which can continuously improve the accuracy and adaptability of the gait. , and obtain the optimal gait parameters; based on the gait model with the optimal gait parameters, the initial gait pattern of the quadruped robot dog is obtained, which is highly scientific and reliable. 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 and cost of tests on actual quadruped robot dogs. The initial gait pattern optimized by 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] Obtaining hardware characteristic parameters of the quadruped robot dog, wherein the hardware characteristic parameters include joint performance, limb structure, and drive system of the quadruped robot dog;

[0092] Obtaining task requirement parameters, wherein the task requirement parameters include motion speed, stability requirements, and energy consumption limits;

[0093] Obtaining environmental constraint parameters, wherein the environmental constraint parameters include terrain complexity, ground material, and weather conditions;

[0094] The β value is determined based on the hardware characteristic parameters, task requirement parameters and environmental constraint parameters of the quadruped robot dog.

[0095] In this embodiment, by obtaining the hardware characteristic parameters of the quadruped robot dog, such as joint performance, limb structure, drive system, etc., its physical characteristics and movement capabilities can be fully understood, which helps to ensure that the setting of the β value matches the hardware characteristics of the quadruped robot dog, thereby giving full play to its performance advantages and avoiding waste or excessive use of hardware resources; obtaining task requirement parameters, such as movement speed, stability requirements, energy consumption limits, etc., can clarify 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 needs during walking, such as increasing movement speed, enhancing stability, reducing energy consumption, etc., which helps to improve the execution efficiency and success rate of the quadruped robot dog in complex tasks; obtaining environmental constraint parameters, such as ground The β value can be adjusted to understand the various challenges that the quadruped robot dog may face during walking. By adjusting the β value, the quadruped robot dog can better adapt to these environmental constraints, such as maintaining stability on different terrains and maintaining normal operation in bad weather. This helps to improve the adaptability and survivability of the quadruped robot dog in complex environments. The setting and adjustment of the β value is a dynamic process, which requires comprehensive consideration based on the hardware characteristics, task requirements and environmental constraints of the quadruped robot dog. By continuously optimizing the β value, the performance of the quadruped robot dog can be continuously improved, such as improving walking efficiency, reducing energy consumption, and enhancing stability. This dynamic adjustment mechanism helps to ensure that the quadruped robot dog can maintain the best condition in different scenarios.

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

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

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

[0099] Drive system: can be quantified using parameters such as motor power, torque, speed, etc., while taking into account the transmission ratio and efficiency of the reducer;

[0100] Obtaining task requirement parameters includes:

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

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

[0103] Energy consumption constraints: can be quantified using desired energy consumption levels 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 friction coefficient;

[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 motion state and external environment information, specifically including:

[0109] Install sensors on the quadruped robot dog, including position sensors, force sensors, vision sensors, and environmental sensors;

[0110] Use sensors to monitor position and posture, motion status, and external environment in real time;

[0111] The data from different sensors are integrated and processed to form comprehensive monitoring information.

[0112] In this embodiment, by installing multiple 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 motion state and external environment can be achieved. These sensors can respectively monitor the robot dog's position and posture, motion state (such as speed, acceleration, joint angles, etc.), and external environmental information (such as terrain, obstacles, and weather). By fusing the data from different sensors, more accurate and comprehensive integrated monitoring information can be generated. Data fusion technology can comprehensively consider the data from various sensors, eliminate the errors or uncertainties that may exist in a single sensor, and improve the accuracy and reliability of the monitoring information. The real-time monitoring of the robot dog's motion state and external environmental information can provide 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 motion state can provide real-time feedback for its motion control. By analyzing the motion state data, potential problems during the robot dog's movement, such as joint wear, excessive energy consumption, and unstable movement, can be promptly identified, so that corresponding measures can be taken to optimize and adjust the robot dog.

[0113] Preferably, the method further comprises:

[0114] Based on the preset alarm threshold and comprehensive monitoring information, the robot dog's motion status and environmental parameters are monitored in real time to see if there are 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, through preset alarm thresholds and comprehensive monitoring information, the motion status and environmental parameters of the robot dog can be monitored in real time. Once an abnormality is detected, an alarm signal is immediately issued. This immediacy helps to promptly discover and respond to potential problems, prevent the problems from further deteriorating, and ensure the safety of the robot dog and the smooth progress of the task; by recording and saving abnormal information, technicians can quickly understand the operating status of the robot dog remotely or on-site, reducing the time for troubleshooting, which not only improves the efficiency of fault handling, but also reduces the downtime and maintenance costs caused by faults; by analyzing the data and records of abnormal occurrences, the operating rules and potential problems of the robot dog under different environments and usage conditions can be summarized. This information can be used to optimize the maintenance strategy of the machine, such as formulating a more reasonable maintenance plan, adjusting the maintenance cycle and maintenance content, etc., thereby reducing maintenance costs and extending the service life of the machine.

[0116] An efficient gait control system for a quadruped robot dog based on biomechanical principles, comprising:

[0117] Gait feature acquisition and analysis module: used to collect and analyze the gait characteristics of quadrupeds in nature and build a gait model for a quadruped robot dog using biomechanical principles;

[0118] Gait model simulation and optimization module: based on the gait model, the gait pattern of the quadruped robot dog is optimized by 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 the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized to obtain the final gait pattern of the quadruped robot dog;

[0120] Gait control module: controls the gait of the quadruped robot dog according to the final gait pattern of the quadruped robot dog;

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

[0122]

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

[0124] A computing device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the processor implements any one of the steps of the above-mentioned method for efficiently controlling the gait of a quadruped robot dog based on biomechanical principles.

[0125] A computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the computer program implements the steps of any one of the above-mentioned methods for efficiently controlling the gait of a quadruped robot dog based on biomechanical principles.

[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 in the scope of protection of the present invention.

Claims

1. An efficient gait control method for a quadruped robot dog based on biomechanical principles, characterized in that: include: Collect and analyze the gait characteristics of quadrupeds in nature, and use biomechanical principles to build a gait model for a quadruped robot dog; Based on the gait model, the gait pattern of the quadruped robot dog is optimized by simulation technology to obtain an initial gait pattern of the quadruped robot dog; According to 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; Controlling the gait of the quadruped robot dog according to the final gait pattern of the quadruped robot dog; The gait generation algorithm applies the following calculation formula when optimizing the initial gait pattern: The E opt represents the optimized single-step energy consumption, the E kin represents the kinetic energy consumption of the robot dog in a single step, and the E pot represents the potential energy change of the robot dog in a single step, β is the potential energy influence coefficient, and T step is the single step time of the current gait, the T ref is the single step time of the reference gait.

2. The efficient gait control method of a quadruped robot dog based on biomechanical principles according to claim 1 is characterized in that: The collecting and analyzing the gait characteristics of quadrupeds in nature and constructing a gait model of a quadruped robot dog using biomechanical principles specifically include: Obtain gait data of quadrupeds under different terrain, speed and task conditions; Extracting gait features from the gait data, wherein the gait features include joint angle changes and limb movement trajectories within a gait cycle; Performing statistical analysis on the extracted gait features to obtain the relationship between the gait features and the animal's motor performance, the relationship including step frequency and speed, step length and stability; Based on the principles of biomechanics and combined with the analysis results of the gait characteristics of quadrupeds, a gait model of a quadruped robot dog is constructed.

3. The efficient gait control method of a quadruped robot dog based on biomechanical principles according to claim 2 is characterized in that: The gait model of the quadruped robot dog is constructed based on the biomechanical principles and the analysis results of the gait characteristics of quadruped animals, which specifically includes: Using the kinematics principle and the analysis results of the gait characteristics of quadrupeds, the kinematic relationship between the joints of the quadruped robot dog is established, including forward kinematics and inverse kinematics; Based on the analysis results of dynamics principles and quadruped gait characteristics, the force applied to the quadruped robot dog during movement is analyzed and the dynamics equation is established; The kinematic model and the dynamic model are integrated to obtain the gait model of the quadruped robot dog.

4. The efficient gait control method of a quadruped robot dog based on biomechanical principles according to claim 3 is characterized in that: Based on the gait model, the gait pattern of the quadruped robot dog is optimized by simulation technology to obtain the initial gait pattern of the quadruped robot dog, which specifically includes: Build a virtual model of a quadruped robot dog in the simulation tool and set the simulation environment parameters; Importing the gait model into a simulation environment, and allowing the quadruped robot dog to move according to the gait model in the virtual environment; During the simulation, the motion data of the quadruped robot dog is collected, wherein the motion data includes joint angle, velocity, acceleration, and ground reaction force; Analyze the collected motion data, and optimize the parameters of the gait model based on the analysis results to obtain the optimal gait parameters; According to the gait model with the optimal gait parameters, the initial gait pattern of the quadruped robot dog is obtained.

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

6. The efficient gait control method of 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 motion state and external environment information, specifically including: Install sensors on the quadruped robot dog, including position sensors, force sensors, visual sensors, and environmental sensors; Use sensors to monitor position and posture, motion status and external environment in real time; The data from different sensors are integrated and processed to form comprehensive monitoring information.

7. The efficient gait control method of a quadruped robot dog based on biomechanical principles according to claim 6, characterized in that: The method further comprises: According to the preset alarm threshold and comprehensive monitoring information, the robot dog's motion state and environmental parameters are monitored in real time to see if there are any abnormalities. When an abnormality occurs, an alarm signal is issued and the time, location and specific information of the abnormality are recorded.

8. An efficient gait control system for a quadruped robot dog based on biomechanical principles, characterized in that: include: Gait feature collection and analysis module: used to collect and analyze the gait features of quadrupeds in nature, and build a gait model of a quadruped robot dog using biomechanical principles; Gait model simulation and optimization module: based on the gait model, the gait pattern of the quadruped robot dog is optimized by simulation technology to obtain the initial gait pattern of the quadruped robot dog; Gait pattern optimization module: based on the gait generation algorithm and the hardware characteristics of the quadruped robot dog, the initial gait pattern is optimized to obtain the final gait pattern of the quadruped robot dog; Gait control module: gait control of the quadruped robot dog according to the final gait pattern of the quadruped robot dog; The gait generation algorithm applies the following calculation formula when optimizing the initial gait pattern: The E opt represents the optimized single-step energy consumption, the E kin represents the kinetic energy consumption of the robot dog in a single step, and the E pot represents the potential energy change of the robot dog in a single step, β is the potential energy influence coefficient, and T step is the single step time of the current gait, the T ref is the single step time of the reference gait.

9. A computing device, characterized in that The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, 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 to 7 are implemented.

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 to 7.

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