Title :
An adaptive artificial potential function approach for geometric sensing
Author :
Zhang, Guoxian ; Ferrari, Silvia
Abstract :
In this paper, a novel artificial potential function is proposed for planning the path of a robotic sensor in a partially observed environment containing multiple obstacles and multiple targets. The sensor planning problem considered in this paper consists of planning the motion of a robot with an on-board sensor that is deployed in order to support a sensing objective, such as, target detection and classification, by gathering sensor measurements over time. An adaptive potential function approach is presented such that the sensor path accounts for prior information on the target geometry and information profit, by traveling a minimum distance.
Keywords :
mobile robots; object detection; path planning; pattern classification; sensors; adaptive artificial potential function approach; geometric sensing; motion planning; multiple obstacles; multiple targets; onboard sensor; partially observed environment; path planning; robotic sensor; sensor planning problem; target classification; target detection; Computational geometry; Information geometry; Motion measurement; Motion planning; Object detection; Orbital robotics; Path planning; Robot sensing systems; Solid modeling; Time measurement;
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
DOI :
10.1109/CDC.2009.5399490
