.png){kind=icon}
返回
Navigation in Multi-Agent System With Side Preference Path Optimizer
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2021.3104470.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Multi-agent path planning aims to find a set of collision-free global path in the joint configuration space to move each agent from the given start states to the goal states and keep the total cost of the path to a minimum. However, the multi-agent systems in the real-world turn out to be a non-communication and partially observable system where the goal states and the planning strategy of other agents are usually unknown. In order to solve the multi-agent path planning problem in a more general environment, a social-aware navigation method is proposed in this paper. By imitating the most basic human road rules, left/right-handed rules, we add side preference to the global path planning by using a path optimizer so that each agent only needs to consider its own planning while the system is approximately optimal. The proposed path optimizer is tested in benchmark maps, robot-robot and robot-human interaction environment, respectively. With the side preference path optimizer, the success rate of multi-agent navigation with 6 agents increase from 0% to 78% at the cost of only extra 0.1 seconds planning time. The proposed method makes the navigation in human-robot interaction scenes become easier.
Keyword:
Navigation
Path planning
Planning
Multi-agent systems
Robot kinematics
Collision avoidance
Task analysis
Multi-agent systems
navigation
path planning
social-aware
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
9.8W
被引数:
29.4W
机构
引用论文
Does it take older adults longer than younger adults to perceptually segregate a speech target from a background masker?在感知上将语音目标与背景掩蔽器隔离开来是否需要老年人比年轻人更长的时间？
PREAI
分享收藏Synthesis of CdS hierarchical microspheres and their application in electrochemiluminescence sensing
PREAI
分享收藏Autonomous human-robot proxemics: socially aware navigation based on interaction potential.png)
AUTONOMOUS ROBOTS
AUTONOMOUS ROBOTSIF4.3
PREAI
分享收藏
查看更多内容