A Multi Objective Hybrid Collision-free Optimal Path Finder for Autonomous Robots in Known Static Environments

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Scalable Computing-Practice and Experience Pub Date : 2022-12-24 DOI:10.12694/scpe.v23i4.2049

Kadari Neeraja, G. Narsimha

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引用次数: 1

Abstract

The most important field of robotics study is path planning. Path planning problem in general is an NP-complete problem. Though several attempts have been made using A*, PRM, RRT, and RRT* these algorithms explore too many nodes in the state space, not completely captured kinematic constraints, and are not optimal in real-time. In this paper, a Multi-Objective Hybrid Collision- free Optimal Path Finder (MOHC-OPF) is proposed which is an attempt to obtain a near-optimal solution by exploring fewer nodes compare to the above existing methods while considering kinematic constraints aiming to generate optimal drivable paths. The empirical study revealed that the proposed algorithm is capable of detecting static obstacles and finding a collision-free nearest-optimal, smooth and safe path to the destination in a static known environment. Multiple criteria, including path length, collision-free, execution time, and smooth path, are used to determine an optimal path.. The proposed algorithm shows efficiency in finding the shortest path length and execution time decreased in 90% of the experiments.

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已知静态环境下自主机器人多目标混合无碰撞最优寻径器

机器人研究中最重要的领域是路径规划。路径规划问题一般是np完全问题。尽管使用A*， PRM, RRT和RRT*进行了多次尝试，但这些算法在状态空间中探索了太多节点，没有完全捕获运动学约束，并且不是实时最优的。本文提出了一种多目标混合无碰撞最优寻径器(MOHC-OPF)，它在考虑运动约束的情况下，以生成最优可驾驶路径为目标，通过比现有方法探索更少的节点来获得接近最优解。实证研究表明，该算法能够检测到静态障碍物，并在静态已知环境中找到一条无碰撞的最优、平滑、安全的路径到达目的地。在确定最优路径时，考虑了路径长度、是否发生碰撞、执行时间、路径是否平滑等因素。在90%的实验中，该算法在最短路径长度的查找效率和执行时间上都有所下降。

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来源期刊

Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.00

自引率

0.00%

发文量

期刊介绍： The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.