Vision-based moving target interception with a mobile robot based on motion prediction and online planning

Xuebo Zhang, Yongxin Wang, Yongchun Fang
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引用次数: 6

Abstract

In this paper, a vision-based moving target interception approach is proposed based on motion prediction and online path and velocity planning. For motion prediction, a fusion method of two motion prediction approaches with historical motion data is proposed to forecast the robot motion. With the predicted target pose as the subgoal, an optimal path is selected from a set of the third order Bezier curves based on their length and curvature cost. Finally, the control input can be calculated through the curvature function from the generated path. Simulation results show the effectiveness of the proposed method. The seamless integration of motion prediction and online planning makes the moving target interception more efficient and predictable.
基于运动预测和在线规划的移动机器人视觉运动目标拦截
本文提出了一种基于运动预测和在线路径速度规划的基于视觉的运动目标拦截方法。在运动预测方面,提出了一种结合历史运动数据的两种运动预测方法的融合方法来预测机器人的运动。以预测的目标位姿为子目标,根据三阶Bezier曲线的长度和曲率代价从一组曲线中选择最优路径。最后,由生成的路径通过曲率函数计算控制输入。仿真结果表明了该方法的有效性。运动预测与在线规划的无缝结合,提高了拦截运动目标的效率和可预见性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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