Research Statement

My long-term research goal is to develop a methodology for robust real-time decision-making in autonomous systems. To achieve this goal, my students and I research novel decision-making algorithms and use these algorithms to build planning modules that enable complex robotic systems to operate autonomously. Our approach is currently based on pushing the limits of graph search-based planning. Conventional wisdom in the robotics community is that graph search approaches cannot provide real-time performance guarantees, do not scale to higher-dimensional problems, and cannot deal with problems that involve uncertainty. My group develops graph search algorithms that are capable of solving challenging problems in robotics in real-time while still maintaining all the positive properties of graph search algorithms such as generality, cost minimization and rigorous guarantees on completeness and quality of solutions. We then use these algorithms to build real-time planners and demonstrate them on physical robots performing such tasks as autonomous navigation, autonomous flight and landing, autonomous mobile manipulation and others. Through our work on building actual planners for physical robots, we have found that it is im-portant to link tightly research on graph search algorithms with the work on deriving the “right” representations of planning problems. The representation needs to encode the planning problem i