倪杭, 王贺升, 陈卫东. 基于软体机器人冗余自由度的实时避障位置控制[J]. 机器人, 2017, 39(3): 265-271. DOI: 10.13973/j.cnki.robot.2017.0265
引用本文: 倪杭, 王贺升, 陈卫东. 基于软体机器人冗余自由度的实时避障位置控制[J]. 机器人, 2017, 39(3): 265-271. DOI: 10.13973/j.cnki.robot.2017.0265
NI Hang, WANG Hesheng, CHEN Weidong. Real-time Obstacle Avoidance and Position Control for a Soft Robot Based on Its Redundant Freedom[J]. ROBOT, 2017, 39(3): 265-271. DOI: 10.13973/j.cnki.robot.2017.0265
Citation: NI Hang, WANG Hesheng, CHEN Weidong. Real-time Obstacle Avoidance and Position Control for a Soft Robot Based on Its Redundant Freedom[J]. ROBOT, 2017, 39(3): 265-271. DOI: 10.13973/j.cnki.robot.2017.0265

基于软体机器人冗余自由度的实时避障位置控制

Real-time Obstacle Avoidance and Position Control for a Soft Robot Based on Its Redundant Freedom

  • 摘要: 研究了如何利用软体机器人空间运动的冗余性,解决控制末端位置时环境中存在障碍物的问题.首先建立了软体机器人的运动学分段常曲率模型,设计了实现实时避障和末端位置控制双重任务的控制算法.算法中在障碍区周围划分警戒区,基于机械臂上标记点的位置反馈,分别给出末端无碰撞风险时的运动策略,以及当末端和中间点进入警戒区时的运动策略,并利用雅可比矩阵的广义逆求出应施加的控制变量.利用李亚普诺夫定理证明了逆雅可比法控制的稳定性.最后,在2维空间进行了实验,结果显示末端可以到达目标点,并且末端与机械臂体能够避开障碍物,验证了避障算法的有效性和位置控制的稳定性.

     

    Abstract: The problem of obstacle avoidance for a soft robot is studied by using the motion redundancy of the soft robot when the tip of the soft robot is controlled to the desired position. The kinematic model of the soft robot based on piecewise constant curvature hypothesis is established. And a controller for both position control of the tip and real-time obstacle avoidance is designed based on this model. In the algorithm, a warning zone is artificially divided around the obstacle. With the position feedback of the marker points on the soft robot, the moving strategy of the tip when it's outside the warning zone, and the moving strategies of the middle points as well as the tip when they're inside the warning zone are given. The required control parameters are solved by the generalized inverse matrix of the Jacobian matrix. Then the stability of the inverse Jacobian control is verified using Lyapunov theory. Finally, experiments are implemented in 2-D space. The results show that the tip can reach the target point, and meanwhile the soft robotic arm successfully avoids the obstacle, which verifies the effectiveness of the obstacle avoidance algorithm and the stability of position control.

     

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