Title
Safety assessment of robot trajectories for navigation in uncertain and dynamic environments
Abstract
This paper presents a probabilistic framework for reasoning about the safety of robot trajectories in dynamic and uncertain environments with imperfect information about the future motion of surrounding objects. For safety assessment, the overall collision probability is used to rank candidate trajectories by considering the probability of colliding with known objects as well as the estimated collision probability beyond the planning horizon. In addition, we introduce a safety assessment cost metric, the probabilistic collision cost, which considers the relative speeds and masses of multiple moving objects in which the robot may possibly collide with. The collision probabilities with other objects are estimated by probabilistic reasoning about their future motion trajectories as well as the ability of the robot to avoid them. The results are integrated into a navigation framework that generates and selects trajectories that strive to maximize safety while minimizing the time to reach a goal location. An example implementation of the proposed framework is applied to simulation scenarios, that explores some of the inherent computational trade-offs.
Year
DOI
Venue
2012
10.1007/s10514-011-9257-9
Auton. Robots
Keywords
Field
DocType
Robot safety,Safety assessment,Motion planning
Motion planning,Computer vision,Time horizon,Simulation,Computer science,Collision probability,Collision,Artificial intelligence,Probabilistic logic,Perfect information,Robot,Probabilistic framework
Journal
Volume
Issue
ISSN
32
3
0929-5593
Citations 
PageRank 
References 
35
1.39
25
Authors
4
Name
Order
Citations
PageRank
Daniel Althoff11376.47
James J. Kuffner Jr.23709251.45
Dirk Wollherr367360.01
Martin Buss41799159.02