基于人工智能技术的群体救援机器人的开发与评述

JunHan Hu
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引用次数: 0

摘要

救援机器人可以在危险复杂的环境中执行救援任务,保护人类不受伤害,提高救援效率和效果,因此在灾害管理和救援中发挥着越来越重要的作用。本文综述了将人工智能应用于救援机器人团队所需的技术和方法。首先,从仿生机器人的角度探讨了蜂群机器人运动控制的可行性。通过对动物仿生学的分析和常用拓扑结构的比较,强调了团队救援机器人救援的本质,并在此基础上提出了结合环境智能优化拓扑网络的方案。其次,介绍了现有的几种微型机器人,并对其数据加载能力进行了评估。在此基础上,概述了机器人视觉和运动指令的过程。同时,研究人员关注当前主流的机器人运动轨迹算法,研究了从单个机器人的运动路径规划扩展到群体协调运动的算法优化过程。其中包括传统的单元分解算法和结合机器学习提高路径规划效率的算法。最后,对上述方法进行了总结,并对人工智能领域其他可能的可行方法的影响进行了探讨和分析。
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Development and Review of Group Rescue Robots Based on Artificial Intelligence Technology
Rescue robots can perform rescue missions in dangerous and complex environments, protect humans from harm, and improve the efficiency and effectiveness of rescue, thus playing an increasingly important role in disaster management and rescue. This article reviews the technologies and methods required to apply artificial intelligence to rescue robot teams. Firstly, the feasibility of motion control for swarm robots was explored from the perspective of biomimetic robots. Through the analysis of animal biomimetics and the comparison of commonly used topological structures, the nature of team rescue robot rescue is emphasized, and based on this, a scheme for optimizing topological networks by combining environmental intelligence is proposed. Secondly, several existing micro robots were introduced and their data loading capabilities were evaluated. On this basis, the process of robot vision and motion commands was outlined. At the meanwhile, researchers focus on the current mainstream robot motion trajectory algorithms, and study the algorithm optimization process from extending the motion path planning of a single robot to group coordinated motion. This includes traditional cell decomposition algorithms and algorithms combined with machine learning to improve path planning efficiency. Finally, the above methods were summarized, and the impact of other possible feasible methods in the field of artificial intelligence was explored and analyzed.
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