摘要
为实现四足机器人在复杂的地形环境、有限的能量供应和不可预知的干扰下运动稳定,提高四足机器人穿越复杂地形的能力,采用了粒子群优化算法对经典步行步态参数进行优化,提出了一种易于实现、能适应不同地形的探索性步态.所提出的探索步态不需要立体视觉或激光雷达所感测到的任何地形信息,机器人通过IMU传感器和足端力传感器接触地面来感知地形.针对提出的优化方法和步态策略进行了仿真和实验,验证了所提出的探索性步态在穿越不平坦地形时的运动能力.
In order to realize the stable motion of the quadruped robot under the conditions of complex terrain environment,limited energy supply and unpredictable interference,and to improve the ability of the quadruped robot to traverse complex terrain,the particle swarm optimization algorithm was used to optimize the classical walking gait parameters.An exploratory gait was proposed,being of easy implement and adapt to different terrains.Needing not any terrain information sensed by stereo vision or LIDAR,the proposed exploratory gait was arranged with the IMU sensor and the foot force sensor to make the robot sense terrain directly.Several simulations and experiments were carried out for the proposed optimization method and gait strategy,verifying the performance of the proposed exploratory gait on uneven terrain.
作者
赵江波
龚思进
王军政
ZHAO Jiangbo;GONG Sijin;WANG Junzheng(Key Laboratory of Drive and Control of Servo Motion System,Ministry of Industry and Information Technology,Beijing 100081,China;Key Laboratory of Intelligent Control and Decision of Complex Systems,Beijing 100081,China;School of Automation,Beijing Institute of Technology,Beijing 100081,China)
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2022年第4期407-414,共8页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(61773057)。
关键词
四足机器人
步态规划
复杂地形
位姿调整
粒子群算法
quadruped robot
gait planning
complex terrain
pose adjustment
particle swarm optimization(PSO)
