Optimal trajectory planning based on bidirectional spline-RRT∗ for wheeled mobile robot

Priyanka Sudhakara, V. Ganapathy, K. Sundaran
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引用次数: 4

Abstract

This paper proposes a trajectory planning of a mobile robot using bidirectional-Rapidly-exploring Random Tree star [RRT star] algorithm with spline technique. In the proposed method, the basic bidirectional-RRT star algorithm is combined with the spline technique to generate smooth trajectories, which are important for curved path navigation of a wheeled mobile robot. The bidirectional-RRT star tree structure is extended by using a spline method based on a cubic Ferguson's curve. Trajectories that are been generated using the proposed bidirectional spline-RRT star algorithm satisfies direction constraints approach on both source and target positions. This makes the proposed algorithm remarkably unlike from other trajectory planning algorithms. As a result, the paths produced by the mobile robots are sub-optimal, dynamically and geometrically feasible, and satisfy direction constraints approaches. Simulation results that are performed affirm these bidirectional spline-RRT star algorithm properties and show the validity of the proposed algorithm, implying that it can be efficiently applied to trajectory planning of wheeled mobile robot operating in real-time environments.
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基于双向样条rrt *的轮式移动机器人最优轨迹规划
本文提出了一种基于样条技术的双向快速探索随机树星算法的移动机器人轨迹规划方法。该方法将基本的双向rrt星形算法与样条技术相结合,生成光滑轨迹,对轮式移动机器人的曲线路径导航具有重要意义。采用基于三次Ferguson曲线的样条法对双向rrt星树结构进行了扩展。利用双向样条- rrt星形算法生成的轨迹在源位置和目标位置上都满足方向约束方法。这使得该算法明显不同于其他轨迹规划算法。因此,移动机器人生成的路径是次优的、动态可行的和几何可行的,并且满足方向约束方法。仿真结果验证了双向样条- rrt星型算法的有效性,表明该算法可以有效地应用于轮式移动机器人实时环境下的轨迹规划。
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