Paper Info
Title
An efficient hybrid planner in changing environments
Abstract
In this paper, we present a new hybrid motion planner that is capable of exploiting previous planning episodes when confronted with new planning problems. Our approach is applicable when several (similar) problems are successively posed for the same static environment, or when the environment changes incrementally between planning episodes. At the heart of our system lie two low-level motion planners: a fast, but incomplete planner LOCAL, and a computationally costly (possibly resolution) complete planner GLOBAL. When a new planning problem is presented to our planner, an efficient meta-level planner MANAGER decomposes the problem into segments that are amenable to solution by LOCAL. This decomposition is made by exploiting a task graph, in which successful planning episodes have been recorded. In cases where the decomposition fails, GLOBAL is invoked. The key to our planner's success is a novel representation of solution trajectories, in which segments of collision-free paths are associated with the boundary of nearby obstacles. Thus we effectively combine the efficiency of one planner with the completeness of another to obtain a more efficient complete planner.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>
Year
DOI
Venue
1994
10.1109/ROBOT.1994.350920
Proceedings of the 1994 IEEE International Conference on Robotics and Automation
Keywords
Field
DocType
hybrid motion planner,incomplete planner,complete planner,meta-level planner,decomposition,task graph,collision-free paths,efficiency,mobile robots
Motion planning,Graph theory,Graph,Computer science,Planner,Artificial intelligence,Completeness (statistics),Mobile robot
Conference
ISSN
ISBN
Citations 
1050-4729
0-8186-5330-2
5
PageRank 
References 
Authors
3.69
5
3
Name
Order
Citations
PageRank
Michael Barbehenn1767.07
Pang C. Chen28520.60
Seth Hutchinson33373260.24