With the development of human space exploration, the space environment is gradually filled with abandoned satellite debris and unknown micrometeorites, which will seriously affect capture motion of space robot. Hence, a novel fast collision-avoidance trajectory planning strategy for a dual-arm free-floating space robot (FFSR) with predefined-time pose feedback will be mainly studied to achieve micron-level tracking accuracy of end-effector in this paper. However, similar to control, the exponential feedback results in larger initial joint angular velocity relative to proportional feedback. Therefore, a GA-based optimization algorithm is used to reduce the control input, which is just the joint angular velocity. Firstly, a pose-error-based kinematic model of the FFSR will be derived from a control perspective. Then, a cumulative dangerous field (CDF) collision-avoidance algorithm is applied in predefined-time trajectory planning to achieve micron-level collision-avoidance trajectory tracking precision. In the end, a GA-based optimization algorithm is used to optimize the predefined-time parameter to obtain a motion trajectory of low joint angular velocity of robotic arms. The simulation results verify our conjecture and conclusion.
翻译:随着人类空间探索的发展,空间环境将逐渐被废弃的卫星碎片和未知微米热物填满,这将严重影响空间机器人的捕捉运动,因此,对具有预设时间的双臂自由漂移空间机器人(FFSR),将主要研究反馈,以实现本文中终端效应的微级跟踪准确性。不过,与控制类似,指数反馈的结果是比比例反馈更大规模的初始联合角速度。因此,使用基于GA的优化算法来减少控制输入,而控制输入只是联合角速度。首先,将从控制角度出发,为FFSR的双臂自由漂移空间机器人(FFSR)的基于表面空气的动态模型。然后,在预先确定的时间轨迹规划中应用累积的危险场(CDF)碰撞避免算法,以实现微度碰撞避免轨道跟踪精确性。最后,使用基于GA的优化算法,以优化预先定义的时间参数,以获得联合角心轴机器人武器的运动轨迹轨迹。模拟结果结论。