Publications Details
Natural sets in manipulation tasks
A key feature distinguishing robotics from traditional computer science is its connection to the physical world. Robot planning software may use elegant algorithms supported by ironclad analytic proofs, but ultimately nature will decide whether the software output is correct in the sense of accomplishing the task goal. Thus a chief goal of robotics research is to understand and capture this nature in a way that allows algorithmic analysis to produce robust physical results. This is made particularly difficult by the presence of uncertainty, which arises from the inevitable discrepancy between the real task and its idealized computer model. This paper reviews fundamental sets of states, forces, and actions that exist for a broad class of robot manipulation tasks, and ties these sets to past and future approaches to developing robust manipulation planning and execution systems.