可见性图
能见度
规划师
计算机科学
运动规划
代表(政治)
图形
路径(计算)
GSM演进的增强数据速率
在飞行中
人工智能
计算机视觉
机器人
理论计算机科学
地理
数学
正多边形
操作系统
政治
气象学
程序设计语言
法学
政治学
几何学
作者
Fan Yang,Chao Cao,Hongbiao Zhu,Jean Oh,Zhang Ji
出处
期刊:Cornell University - arXiv
日期:2021-10-18
标识
DOI:10.48550/arxiv.2110.09460
摘要
The problem of path planning in unknown environments remains a challenging problem - as the environment is gradually observed during the navigation, the underlying planner has to update the environment representation and replan, promptly and constantly, to account for the new observations. In this paper, we present a visibility graph-based planning framework capable of dealing with navigation tasks in both known and unknown environments. The planner employs a polygonal representation of the environment and constructs the representation by extracting edge points around obstacles to form enclosed polygons. With that, the method dynamically updates a global visibility graph using a two-layered data structure, expanding the visibility edges along with the navigation and removing edges that become occluded by newly observed obstacles. When navigating in unknown environments, the method is attemptable in discovering a way to the goal by picking up the environment layout on the fly, updating the visibility graph, and fast re-planning corresponding to the newly observed environment. We evaluate the method in simulated and real-world settings. The method shows the capability to attempt and navigate through unknown environments, reducing the travel time by up to 12-47% from search-based methods: A*, D* Lite, and more than 24-35% than sampling-based methods: RRT*, BIT*, and SPARS.
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