Title :
Accommodating Uncertainty in Covert and Overt Robot Path Planning
Author :
Marzouqi, Mohamed S. ; Jarvis, Ray A.
Author_Institution :
Intell. Robot. Res. Centre, Monash Univ., Melbourne, VIC
Abstract :
In this paper, the notion of probabilities has been introduced to plan a visibility-based path to cope with real-world uncertainties. A mobile robot needs to either minimize (covert) or maximize (overt) its exposure to an initially known or suspected entities´ positions. Those positions can be inaccurately estimated or have the possibility of change as the entities may move unpredictably. Promising results have been shown when testing the planning technique on a simulated environment. A number of test cases are presented for both covert and overt applications.
Keywords :
mobile robots; path planning; position control; probability; covert robot path planning; mobile robot; position estimation; probability; real-world uncertainty; visibility-based path; Costs; Euclidean distance; Gaussian distribution; Humans; Intelligent robots; Mobile robots; Path planning; Probability distribution; Testing; Uncertainty;
Conference_Titel :
TENCON 2005 2005 IEEE Region 10
Conference_Location :
Melbourne, Qld.
Print_ISBN :
0-7803-9311-2
Electronic_ISBN :
0-7803-9312-0
DOI :
10.1109/TENCON.2005.300870