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.

自主移动机器人（AMR）在制造领域非常流行，特别是在涉及大型工厂车间的过程中，这些机器人用于将物料从一个位置运输到另一个位置。在一个AMR学校要完成多个优先任务的环境中，整个计划问题可以分为三个连续步骤：为AMR学校分配任务，为每个AMR安排任务以及为每个轨迹进行计划个人AMR。本文重点介绍了每个AMR的轨迹生成过程。与仅在路径规划期间仅考虑AMR必须到达的位置的传统方法不同，这里还考虑了AMR的能效。我们介绍了基于物理的AMR模型，以及AMR的能量自觉轨迹生成的最优控制公式。讨论了数值解决此问题的方法，并针对每种提出的算法在大约100个测试用例上给出了结果，并比较了性能和计算效率。结果表明，与常用的最短路径技术相比，所提出的节能方法在能源使用方面表现更好（5-10％），同时保持了相似的计算和操作效率。