A self-adaptive safe A* algorithm for AGV in large-scale storage environment

IF 2.3 4区计算机科学 Q3 ROBOTICS

Intelligent Service Robotics Pub Date : 2024-01-31 DOI:10.1007/s11370-023-00494-2

Xiaolan Wu, Qiyu Zhang, Zhifeng Bai, Guifang Guo

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Abstract

This paper presents a safe A* algorithm for the path planning of automated guided vehicles (AGVs) operating in storage environments. Firstly, to overcome the problems of great collision risk and low search efficiency in the path produced by traditional A* algorithm, a new evaluation function is designed by introducing repulsive term and assigning dynamic adjustment weights to heuristic items. Secondly, a Floyd deletion algorithm based on the safe distance is proposed to remove redundant path points for reducing the path length. Moreover, the algorithm replaces the broken line segments at the turns with a cubic B-spline to ensure the smoothness of turning points. The simulation applied to different scenarios and different specifications showed that, compared with other three typical path planning algorithms, the path planned by the proposed safe A* algorithm always keeps a safe distance from the obstacle and the path length is reduced by 1.95\(\%\), while the planning time is reduced by 25.03\(\%\) and the number of turning point is reduced by 78.07\(\%\) on average.

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大规模仓储环境中 AGV 的自适应安全 A* 算法

本文针对在仓储环境中运行的自动导引车（AGV）的路径规划提出了一种安全的 A* 算法。首先，为了克服传统 A* 算法生成的路径存在碰撞风险大、搜索效率低等问题，本文通过引入斥力项并为启发式项目分配动态调整权重，设计了一种新的评估函数。其次，提出了一种基于安全距离的 Floyd 删除算法，用于删除冗余路径点，以减少路径长度。此外，该算法还用立方 B 样条替换了转弯处的断线段，以确保转弯点的平滑性。不同场景、不同规格的仿真结果表明，与其他三种典型的路径规划算法相比，所提出的安全A*算法规划的路径始终与障碍物保持安全距离，路径长度减少了1.95（\%\），规划时间平均减少了25.03（\%\），转弯点数量平均减少了78.07（\%\）。

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来源期刊

Intelligent Service Robotics ROBOTICS-

CiteScore

5.70

自引率

4.00%

发文量

期刊介绍： The journal directs special attention to the emerging significance of integrating robotics with information technology and cognitive science (such as ubiquitous and adaptive computing,information integration in a distributed environment, and cognitive modelling for human-robot interaction), which spurs innovation toward a new multi-dimensional robotic service to humans. The journal intends to capture and archive this emerging yet significant advancement in the field of intelligent service robotics. The journal will publish original papers of innovative ideas and concepts, new discoveries and improvements, as well as novel applications and business models which are related to the field of intelligent service robotics described above and are proven to be of high quality. The areas that the Journal will cover include, but are not limited to: Intelligent robots serving humans in daily life or in a hazardous environment, such as home or personal service robots, entertainment robots, education robots, medical robots, healthcare and rehabilitation robots, and rescue robots (Service Robotics); Intelligent robotic functions in the form of embedded systems for applications to, for example, intelligent space, intelligent vehicles and transportation systems, intelligent manufacturing systems, and intelligent medical facilities (Embedded Robotics); The integration of robotics with network technologies, generating such services and solutions as distributed robots, distance robotic education-aides, and virtual laboratories or museums (Networked Robotics).