经典路径规划方法与启发式路径规划方法的对抗

Vishal Chand, Avinesh Prasad, K. Chaudhary, B. Sharma, Samlesh Chand
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引用次数: 5

摘要

机器人路径规划是一个计算问题,目的是找到一个有效的配置序列,使机器人从初始位置移动到最终位置。有几种经典的和基于启发式的方法可以用来解决这个问题。本文比较了基于势场的经典方法lyapunov控制方案与标准和超前萤火虫算法的性能。性能比较基于最优路径距离和时间。结果表明,与基于lyapunov的方法相比,步进萤火虫算法在更短的时间内找到了更短的路径。当起点、目标和障碍物的中心坐标共线时,LbCS也固有地面临局部极小问题。使用萤火虫算法解决了这个问题,其中萤火虫的多样化有助于避免局部最小值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Face-off - Classical and Heuristic-based Path Planning Approaches
Robot path planning is a computational problem to find a valid sequence of configurations to move a robot from an initial to a final destination. Several classical and heuristic-based methods exist that can be used to solve the problem. This paper compares the performance of a classical method based on potential field, Lyapunov-based Control Scheme, with those of the standard and stepping ahead Firefly Algorithms. The performance comparison is based on the optimal path distance and time. The results show that the stepping ahead Firefly algorithm finds a shorter path in lesser duration when compared with the Lyapunov-based method. The LbCS also inherently faces the local minima problem when the start, target, and obstacle’s center coordinates are collinear. This problem is solved using the firefly algorithm where the diversification of the fireflies helps escape local minima.
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