| 引用本文: | 高明,唐洪,张鹏.机器人集群路径规划技术研究现状.[J].国防科技大学学报,2021,43(1):127-138.[点击复制] |
| GAO Ming,TANG Hong,ZHANG Peng.Survey of path planning technologies for robots swarm[J].Journal of National University of Defense Technology,2021,43(1):127-138[点击复制] |
|
| |
|
|
| 本文已被：浏览 7716次 下载 6178次 |
| 机器人集群路径规划技术研究现状 |
| 高明1,唐洪2,张鹏3 |
|
(1. 国防科技大学 智能科学学院, 湖南 长沙 410073;2. 国防科技大学 研究生院, 湖南 长沙 410073;3. 国防科技大学 教务处, 湖南 长沙 410073)
|
| 摘要: |
| 受社会型生物群体行为启发,群体智能得到日益广泛的关注,机器人集群作为群体智能的重要承载者得到了大量研发和广泛应用。机器人集群路径规划技术作为一项核心关键技术也得到快速发展。为此全面深入地调研了机器人集群路径规划的技术发展现状,创新性地归纳了适用于不同集群规模、可扩展性要求、通信需求以及算法要求的集群规划基础计算架构,包括冗余计算架构、分布计算架构和分层计算架构。从可扩展性和适用性角度,分类梳理了最适用于机器人集群的路径规划方法,包括仿生学方法、人工势场法、几何学方法、经典搜索法和进化学习法,并为集群仿真验证研究提供了七款可免费下载或开源的机器人集群仿真验证平台。 |
| 关键词: 群体智能 自组织 路径规划 机器人集群 |
| DOI：10.11887/j.cn.202101017 |
| 投稿日期：2019-08-23 |
| 基金项目: |
|
| Survey of path planning technologies for robots swarm |
| GAO Ming1, TANG Hong2, ZHANG Peng3 |
|
(1. College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China;2. Graduate School, National University of Defense Technology, Changsha 410073, China;3. Office of Educational Administration, National University of Defense Technology, Changsha 410073, China)
|
| Abstract: |
| As an important carrier of group intelligence, robot clusters have also received a lot of research and development and more and more applications. Robot cluster path planning technology has also developed rapidly as a core key technology. The technical development status of robot cluster path planning was comprehensively and deeply researched. The basic computing architecture applying to different cluster sizes, scalability requirements, communication requirements, and algorithms of the requirements was innovatively summarized. The basic computing architecture consists of redundant computing architecture, distributed computing architecture, and hierarchical computing architecture. From the perspective of scalability and applicability, the path planning method which takes advantage of the most suitable robot clusters, including bionics, artificial potential field method, geometric method, classical search method and evolutionary learning method, was classified. For the cluster simulation verification research, it provided seven free downloadable or open source robot cluster simulation verification platforms. |
| Keywords: swarm intelligence self-organization path planning robots swarm |
|
|
|
|
|
