Formation obstacle avoidance using RRT and constraint based programming

Fredrik Båberg, Petter Ögren
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引用次数: 2

Abstract

In this paper, we propose a new way of doing formation obstacle avoidance using a combination of Constraint Based Programming (CBP) and Rapidly Exploring Random Trees (RRTs). RRT is used to select waypoint nodes, and CBP is used to move the formation between those nodes, reactively rotating and translating the formation to pass the obstacles on the way. Thus, the CBP includes constraints for both formation keeping and obstacle avoidance, while striving to move the formation towards the next waypoint. The proposed approach is compared to a pure RRT approach where the motion between the RRT waypoints is done following linear interpolation trajectories, which are less computationally expensive than the CBP ones. The results of a number of challenging simulations show that the proposed approach is more efficient for scenarios with high obstacle densities.
基于RRT和约束规划的编队避障算法
本文提出了一种基于约束规划(CBP)和快速探索随机树(RRTs)相结合的编队避障方法。RRT用于选择航点节点,CBP用于在这些节点之间移动编队,反应性地旋转和平移编队以通过途中的障碍物。因此,CBP包括编队保持和避障约束,同时努力将编队移动到下一个航路点。该方法与纯RRT方法进行了比较,其中RRT路径点之间的运动遵循线性插值轨迹,这比CBP方法的计算成本更低。大量具有挑战性的仿真结果表明,该方法对于高障碍物密度的场景更有效。
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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