Path planning for storage robots using the RRT algorithm

Abstract

This paper delves into the issue of storage robot path planning, a critical challenge in the field of warehouse automation. To address this challenge, this paper introduces the Rapidly-exploring Random Tree (RRT) algorithm and presents an innovative path planning approach aimed at efficiently handling dynamic environments and multiple constraints.Firstly, this paper extensively explores the complexity of the storage robot path planning problem, emphasizing its crucial nature in practical applications. Next, it provides an in-depth explanation of the principles of the RRT algorithm, particularly highlighting its unique advantages in path planning, especially in high-dimensional spaces and nonlinear constraints. In the implementation section, a detailed description is provided on how to apply the RRT algorithm to storage robot path planning, including the workflow of the algorithm and its key steps.In the discussion section, this paper thoroughly analyzes the potential application value of the RRT algorithm in storage robot path planning and discusses future improvement directions and research areas. Finally, by summarizing the outcomes of this study, the paper emphasizes the pivotal role of the RRT algorithm in storage robot path planning and the positive impact it brings to solving this significant problem.