A Systematic Approach to Robot Task and Motion Planning in Belief Space

Robots have the potential for wide-ranging positive impacts on society in complex or dangerous applications such as disaster relief, elder care and the reshoring of manufacturing jobs. However, existing robots have had limited success is these domains, mainly because the planning and control algorithms are not robust to misconceptions in the robot's "understanding" of its environment nor to small imperfections in the robot's ability to execute the required actions. The overall goal of this project is to develop the sensing, planning, and control algorithms necessary to overcome these problems, and hence necessary to allow robots to work productively in complex domains shared with humans.

The key activities of this project are the development of new ways of representing uncertainty in the state of the world that support efficient planning for robots. These new representations and algorithms provide principled and practical methods of integrating perception and action in complex domains. The resulting algorithms are tested in the context of a real robot performing household tasks in a kitchen environment.

The project also involves a thorough integration of research and education. Graduate and undergraduate students are involved in all aspects of the research. Furthermore, the research in this project forms the basis of an undergraduate subject on robot planning algorithms under development at MIT.