Safe navigation in dynamic, unknown, continuous, and cluttered environments

Mike D'Arcy, Pooyan Fazli, D. Simon
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引用次数: 7

Abstract

We introduce ProbLP, a probabilistic local planner, for safe navigation of an autonomous robot in dynamic, unknown, continuous, and cluttered environments. We combine the proposed reactive planner with an existing global planner and evaluate the hybrid in challenging simulated environments. The experiments show that our method achieves a 77% reduction in collisions over the straight-line local planner we use as a benchmark.
在动态、未知、连续和混乱的环境中安全导航
本文介绍了概率局部规划器ProbLP,用于自主机器人在动态、未知、连续和杂乱环境中的安全导航。我们将所提出的响应式规划器与现有的全局规划器相结合,并在具有挑战性的模拟环境中对其进行了评估。实验表明,我们的方法比我们用作基准的直线局部规划器减少了77%的碰撞。
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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