Seminar - Geoff Hollinger Feb. 1

There is growing interest in the use of robots to gather information from natural environments. Examples include biological monitoring, mine sweeping, oil spill cleanup, and seismic event detection. The increasing capabilities of the robots themselves enable more sophisticated decision making techniques that optimize information gathered and adapt as new information is received. The question becomes: how do we develop path planning methods for information gathering tasks capable of dealing with the communication limitations, noisy sensing, and mobility restrictions present in natural environments? This talk considers two problems related to path planning for Autonomous Underwater Vehicles (AUVs): (1) data gathering from an underwater sensor network equipped with acoustic modems and (2) multi-vehicle ocean search using limited communication. For the first problem, I present path planning methods that extend algorithms for variants of the Traveling Salesperson Problem (TSP) and integrate these techniques with realistic acoustic communication modeling. For the second problem, I discuss coordination methods that combine receding horizon planning with submodular optimization and show how these methods can be distributed using novel data fusion techniques. I provide analysis of each aspect of these problems using principled approximations, which gives us new insight into the underlying structure of active sensing problems. Finally, I present experiments that demonstrate the high performance of the proposed solutions versus the state of the art in robot path planning.