Please use this identifier to cite or link to this item: https://doi.org/10.1109/ROBOT.2008.4543611
Title: A point-based POMDP planner for target tracking
Authors: Hsu, D. 
Lee, W.S. 
Rong, N.
Issue Date: 2008
Citation: Hsu, D., Lee, W.S., Rong, N. (2008). A point-based POMDP planner for target tracking. Proceedings - IEEE International Conference on Robotics and Automation : 2644-2650. ScholarBank@NUS Repository. https://doi.org/10.1109/ROBOT.2008.4543611
Abstract: Target tracking has two variants that are often studied independently with different approaches: target searching requires a robot to find a target initially not visible, and target following requires a robot to maintain visibility on a target initially visible. In this work, we use a partially observable Markov decision process (POMDP) to build a single model that unifies target searching and target following. The POMDP solution exhibits interesting tracking behaviors, such as anticipatory moves that exploit target dynamics, information-gathering moves that reduce target position uncertainty, and energy-conserving actions that allow the target to get out of sight, but do not compromise long-term tracking performance. To overcome the high computational complexity of solving POMDPs, we have developed SARSOP, a new point-based POMDP algorithm based on successively approximating the space reachable under optimal policies. Experimental results show that SARSOP is competitive with the fastest existing point-based algorithm on many standard test problems and faster by many times on some. ©2008 IEEE.
Source Title: Proceedings - IEEE International Conference on Robotics and Automation
URI: http://scholarbank.nus.edu.sg/handle/10635/40621
ISBN: 9781424416479
ISSN: 10504729
DOI: 10.1109/ROBOT.2008.4543611
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

46
checked on Aug 10, 2018

WEB OF SCIENCETM
Citations

18
checked on Jul 16, 2018

Page view(s)

64
checked on Apr 21, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.