DocumentCode :
3597336
Title :
PAO for planning with hidden state
Author :
Ferguson, Dave ; Stentz, Anthony ; Thrun, Sebastian
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume :
3
fYear :
2004
Firstpage :
2840
Abstract :
We describe a heuristic search algorithm for generating optimal plans in a new class of decision problem, characterised by the incorporation of hidden state. The approach exploits the nature of the hidden state to reduce the state space by orders of magnitude. It then interleaves heuristic expansion of the reduced space with forwards and backwards propagation phases to produce a solution in a fraction of the time required by other techniques. Results are provided on an outdoor path planning application.
Keywords :
backpropagation; decision making; mobile robots; path planning; search problems; backwards propagation; decision problem; heuristic expansion; heuristic search algorithm; optimal plan generation; outdoor path planning; state space; Costs; Indoor environments; Mobile robots; Orbital robotics; Path planning; Probability density function; Satellite navigation systems; Space vehicles; State-space methods; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2004. Proceedings. ICRA '04. 2004 IEEE International Conference on
ISSN :
1050-4729
Print_ISBN :
0-7803-8232-3
Type :
conf
DOI :
10.1109/ROBOT.2004.1307491
Filename :
1307491
Link To Document :
بازگشت