Cooperative Search of Multiple Unknown Transient Radio Sources Using Multiple Paired Mobile Robots

We develop a localization method to enable a team of mobile robots to search for multiple unknown transient radio sources. Because of signal source anonymity, short transmission durations, and dynamic transmission patterns, robots cannot treat the radio sources as continuous radio beacons. Moreover,...

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Bibliographic Details
Published in:IEEE transactions on robotics 2014-10, Vol.30 (5), p.1161-1173
Main Authors: Kim, Chang-Young, Song, Dezhen, Xu, Yiliang, Yi, Jingang, Wu, Xinyu
Format: Article
Language:English
Subjects:
Algorithms
Data transmission
Detection
Entropy
Mobile robots
Planning
Position (location)
Probability
Radio communications
Radio localization
Radio signals
Robot kinematics
robot motion planning
Robot sensing systems
Robots
Searching
Signal strength
Simulation
Transient analysis
unknown sensor network
Walking
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Summary:We develop a localization method to enable a team of mobile robots to search for multiple unknown transient radio sources. Because of signal source anonymity, short transmission durations, and dynamic transmission patterns, robots cannot treat the radio sources as continuous radio beacons. Moreover, robots do not know the source transmission power and have limited sensing ranges. To cope with these challenges, we pair up robots and develop a cooperative sensing model using signal strength ratios from the paired robots. We formally prove that the joint conditional posterior probability of source locations for the m-robot team can be obtained by combining the pairwise joint posterior probabilities, which can be derived from signal strength ratios. Moreover, we propose a pairwise ridge walking algorithm (PRWA) to coordinate the robot pairs based on the clustering of high-probability regions and the minimization of local Shannon entropy. We have implemented and validated the algorithm under both the hardware-driven simulation and physical experiments. Experimental results show that the PRWA-based localization scheme consistently outperforms the other four heuristics.
ISSN:1552-3098
1941-0468
DOI:10.1109/TRO.2014.2333097