TY - GEN
T1 - Monte carlo simultaneous localization of multiple unknown transient radio sources using a mobile robot with a directional antenna
AU - Song, Dezhen
AU - Kim, Chang Young
AU - Yi, Jingang
PY - 2009
Y1 - 2009
N2 - We report our system and algorithm developments that enable a single mobile robot equipped with a directional antenna to simultaneously localize multiple unknown transient radio sources. Due to signal source anonymity, short transmission durations, and dynamic transmission patterns the robot cannot treat the radio sources as continuous radio beacons.We model the radio source behaviors using a novel spatiotemporal probability occupancy grid (SPOG) that captures transient characteristics of radio transmissions and tracks the spatiotemporal posterior probability distribution of the radio transmissions. As a Monte Carlo method, we propose a ridge walking motion planning algorithm that enables the robot to efficiently traverse the high probability regions to accelerate the convergence of the posterior probability distribution. We have implemented the algorithms and the experiment results show that our method consistently outperforms methods such as arandom walk or a fixed-route patrol mechanism.
AB - We report our system and algorithm developments that enable a single mobile robot equipped with a directional antenna to simultaneously localize multiple unknown transient radio sources. Due to signal source anonymity, short transmission durations, and dynamic transmission patterns the robot cannot treat the radio sources as continuous radio beacons.We model the radio source behaviors using a novel spatiotemporal probability occupancy grid (SPOG) that captures transient characteristics of radio transmissions and tracks the spatiotemporal posterior probability distribution of the radio transmissions. As a Monte Carlo method, we propose a ridge walking motion planning algorithm that enables the robot to efficiently traverse the high probability regions to accelerate the convergence of the posterior probability distribution. We have implemented the algorithms and the experiment results show that our method consistently outperforms methods such as arandom walk or a fixed-route patrol mechanism.
UR - http://www.scopus.com/inward/record.url?scp=70350365094&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70350365094&partnerID=8YFLogxK
U2 - 10.1109/ROBOT.2009.5152557
DO - 10.1109/ROBOT.2009.5152557
M3 - Conference contribution
AN - SCOPUS:70350365094
SN - 9781424427895
T3 - Proceedings - IEEE International Conference on Robotics and Automation
SP - 3154
EP - 3159
BT - 2009 IEEE International Conference on Robotics and Automation, ICRA '09
T2 - 2009 IEEE International Conference on Robotics and Automation, ICRA '09
Y2 - 12 May 2009 through 17 May 2009
ER -