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Maryland Robotics Student Seminar: Distributed Multi-Robot Information Gathering using Path-Based Se Distributed Multi-Robot Information Gathering using Path-Based Sensors in Entropy-Weighted Voronoi Regions Alkesh Kumar Srivastava Maryland Applied Graduate Engineering Department Advisor: Dr. Michael Otte University of Maryland Abstract Distributed information-gathering algorithms for multi-robot systems that use multiple path-based sensors to infer the locations of hazards within the environment will be discussed. Path-based sensors output binary observations, reporting whether or not an event (like robot destruction) has occurred somewhere along a path, but without the ability to discern where an event has occurred along a path. Prior work has shown that path-based sensors can be used for search and rescue in hazardous communication-denied environments—sending robots into the environment one at a time. We extend this idea to enable multiple robots to search the environment simultaneously. The search space contains targets (human survivors) amidst hazards that can destroy robots (triggering a path-based hazard sensor). We consider a case where communication from the field is prohibited due to communication loss, jamming, or stealth. The search effort is distributed among multiple robots using an entropy-weighted Voronoi partitioning of the environment, such that during each search round, all regions have approximately equal information entropy. In each round, every robot is assigned a region in which its search path is calculated. Numerical Monte Carlo simulations are used to compare this idea to other ways of using path-based sensors on multiple robots. The experiments show that information gathering using entropy-weighted Voronoi partitioning outperforms the other methods in terms of the information gathered and computational cost. About the Robotics Student Seminars The purpose of these talks is to:
**Light refreshments will be served.
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