Energy-Conscientious Trajectory Planning for an Autonomous Mobile Robot in an Asymmetric Task Space

Abstract

Autonomous Mobile Robots (AMRs) have become extremely popular in the manufacturing domain, especially for processes involving large factory floors where these robots are used for transporting materials from one location to another. In an environment where there are multiple prioritized tasks to be completed by a school of AMRs, the overall planning problem can be broken down into three sequential steps: task allocation for the school of AMRs, task scheduling for each AMR, and trajectory planning for each individual AMR. This paper focuses on the trajectory generation procedure for each AMR. Unlike traditional approaches that only consider the location an AMR has to travel to during path planning, here, energy efficiency of the AMR is also considered. We present the physics-based model of the AMR as well as an optimal control formulation for energy-conscientious trajectory generation for the AMR. Methods to numerically solve this problem are discussed, and results are presented for each proposed algorithm on approximately 100 test cases, comparing both performance and computational efficiency. The results show that the presented energy-conscientious methods perform better in terms of energy usage (5-10%) compared to commonly-used shortest path techniques while maintaining similar computational and operational efficiency.