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CARING: Communication-Aware Robotic Information Gathering
This thesis presents information measures, utility design, and its distributed optimizations for decision making of communication-aware robotic information gathering (CARING). Firstly, this thesis presents a novel information flow to formulate CARING problems with a global utility. The global utility is designed based on communication-aware mutual information, which implies how much each robot receives information over communication. An approach to computing non-Gaussian distribution information under a packet erasure channel addresses utility computation issues. The method formulates communication-aware informative measures by considering communication and sensor dynamics without decoupling assumptions. Next, this thesis describes two local utilities to solve the CARING problem in a distributed way. One of which is the marginal contribution from the global utility, and the other is the selfish contribution that divides the global utility by robots. This thesis then analyzes the local utilities in terms of optimality performance guarantee and computational complexity by using information range and optimization dominance by one of the information components. Three approaches to design distributed optimizations for communication-aware are presented. The first approach is a communication-aware sequential greedy (SG) approach that robots solve their local utility with delivered decisions from higher rank robots in the hierarchy. Another method is the decision iteration with neighbors (DIN), in which robots solve given all delivered decisions and share its result with neighbors. The other is the decision iteration with the best response (DIBR), a similar procedure with DIN with the best response prediction of non-neighbors to improve the optimization performance. Combined approaches of local utilities and distributed optimizations are assessed using optimality performance and computational properties. Finally, this thesis demonstrates using a Gazebo/ROS-based simulation. The simulation uses a practical wireless transceiver module validated by real flight data