Paper Info
Title
Planning with movable obstacles in continuous environments with uncertain dynamics
Abstract
In this paper we present a decision theoretic planner for the problem of Navigation Among Movable Obstacles (NAMO) operating under conditions faced by real robotic systems. While planners for the NAMO domain exist, they typically assume a deterministic environment or rely on discretization of the configuration and action spaces, preventing their use in practice. In contrast, we propose a planner that operates in real-world conditions such as uncertainty about the parameters of workspace objects and continuous configuration and action (control) spaces. To achieve robust NAMO planning despite these conditions, we introduce a novel integration of Monte Carlo simulation with an abstract MDP construction. We present theoretical and empirical arguments for time complexity linear in the number of obstacles as well as a detailed implementation and examples from a dynamic simulation environment.
Year
DOI
Venue
2013
10.1109/ICRA.2013.6631116
Robotics and Automation
Keywords
Field
DocType
Monte Carlo methods,collision avoidance,computational complexity,decision theory,robot dynamics,Monte Carlo simulation,NAMO domain,NAMO planning,abstract MDP construction,action spaces,continuous environments,decision theoretic planner,deterministic environment,dynamic simulation environment,linear time complexity,movable obstacle planning,navigation among movable obstacles,real robotic systems,real-world conditions,uncertain dynamics,workspace object configuration
Discretization,Mathematical optimization,Computer science,Workspace,Planner,Control engineering,Artificial intelligence,Decision theory,Time complexity,Robot,Dynamic simulation,Computational complexity theory
Conference
Volume
Issue
ISSN
2013
1
1050-4729
ISBN
Citations 
PageRank 
978-1-4673-5641-1
3
0.42
References 
Authors
13
3
Name
Order
Citations
PageRank
Martin Levihn1244.12
Scholz, Jonathan21045.42
Mike Stilman350737.01