ROBOTIC MOTION PLANNING USING CONVEX OPTIMIZATION METHODS

T. Nayl
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Abstract

Collision avoidance techniques tend to derive the robot away of the obstacles in minimal total travel distance. Most ofthe collision avoidance algorithms have trouble get stuck in a local minimum. A new technique is to avoid local minimum in convexoptimization-based path planning. Obstacle avoidance problem is considered as a convex optimization problem under system state andcontrol constraints. The idea is by considering the obstacles as a convex set of points which represents the obstacle that encloses inminimum volume ellipsoid, also the addition of the necessary offset distance and the modified motion path is presented. In the analysis,the results demonstrated the effectiveness of the suggested motion planning by using the convex optimization technique.
机器人运动规划的凸优化方法
避碰技术倾向于使机器人以最小的总移动距离远离障碍物。大多数避碰算法都有陷入局部最小值的问题。在基于凸优化的路径规划中,避免局部最小值是一种新的方法。将避障问题看作是在系统状态和控制约束下的凸优化问题。其思想是将障碍物视为一个点的凸集,表示包围最小体积椭球的障碍物,并添加必要的偏移距离和修改的运动路径。分析结果表明,采用凸优化技术进行运动规划是有效的。
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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