The chief complication is uncertainty. Objects are never exactly where they should be, nor are they exactly the right shape. Also, the robot's motions are imprecise, the sensors are noisy, and all of the relevant physical parameters, such as the coefficient of friction, are hard to predict. Underlying both of these options, a robot must include uncertainty in its model of objects and physical processes. We have built planners that manipulate simple shapes in two-dimensional worlds, and have demonstrated the systems using an industrial robot in the Manipulation Laboratory .
Manipulation takes place in a world often dominated by friction and collisions.
Combined with our interest in uncertainty, these novel aspects have generated interesting new problems in classical mechanics. In collaboration with Tom Mitchell, we are working on a robot that will watch the world and use its observations to revise its model. Such incremental adjustments to the model may partly explain how performance improves with experience. Robotics Education Lab - The Robotics Education Lab is a central resource to support courses and individual projects in robotics. The Robotics Institute is part of the School of Computer Science , Carnegie Mellon University .