李志海, 付宜利. 基于遗传算法的仿生双足爬壁机器人越障运动规划[J]. 机器人, 2012, 34(6): 751-757. DOI: 10.3724/SP.J.1218.2012.00751
引用本文: 李志海, 付宜利. 基于遗传算法的仿生双足爬壁机器人越障运动规划[J]. 机器人, 2012, 34(6): 751-757. DOI: 10.3724/SP.J.1218.2012.00751
LI Zhihai, FU Yili. Motion Planning of a Bio-inspired Biped Wall Climbing Robot Stepping over Obstacles Based on Genetic Algorithm[J]. ROBOT, 2012, 34(6): 751-757. DOI: 10.3724/SP.J.1218.2012.00751
Citation: LI Zhihai, FU Yili. Motion Planning of a Bio-inspired Biped Wall Climbing Robot Stepping over Obstacles Based on Genetic Algorithm[J]. ROBOT, 2012, 34(6): 751-757. DOI: 10.3724/SP.J.1218.2012.00751

基于遗传算法的仿生双足爬壁机器人越障运动规划

Motion Planning of a Bio-inspired Biped Wall Climbing Robot Stepping over Obstacles Based on Genetic Algorithm

  • 摘要: 针对仿生双足爬壁机器人的壁面越障运动,提出一种基于遗传算法的越障运动规划算法.该算法在分析机器人稳定运动条件和障碍物笛卡儿空间几何约束的基础上,通过加权系数法定义适应度函数,使机器人稳定裕度和运动代价在某种程度上达到综合最优.对笛卡儿位姿进行编码,在笛卡儿空间和关节空间约束下,规划出一条无碰撞、稳定性高的机器人运动序列.利用该算法对机器人跨越凸起障碍物运动进行规划仿真,结果证明该方法可保证机器人运动的稳定裕度和运动轨迹的平滑.

     

    Abstract: For obstacle stepping over of a bio-inspired biped wall climbing robot, a motion planning algorithm based on genetic algorithm is proposed. By analyzing stability requirements and geometrical constraints of obstacle avoidance in Cartesian space, a fitness function is defined with a weighted coefficient method, so that the stability margin and movement cost can attain integrated optimum to a certain extent. By coding its posture in Cartesian space, a collision-free and highly stable motion sequence for the robot is planned, under the constraints in Cartesian space and joint space. Motion planning of the robot stepping over protruding obstacles is implemented in simulation with the proposed algorithm. Results show that the algorithm can guarantee the stability margin of robot motion and the smoothness of the trajectory.

     

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