By Dmitry Berenson | Robotics Institute, Carnegie Mellon University | May, 2011
Every planning problem in robotics involves constraints. Whether the robot must avoid collision or joint limits, there are always states that are not permissible.Some constraints are straightforward to satisfy while others can be so stringent that feasible states are very difficult to find. What makes planning with constraints challenging is that, for many constraints, it is impossible or impractical to provide the planning algorithm with the allowed states explicitly; it must discover these states as it plans. The goal of this thesis is to develop a framework for representing and exploring feasible states in the context of manipulation planning.