The role of vision in two-arm manipulation is investigated in order to suggest a qualitative approach for the solution of coordinated manipulative actions. The visuomotor behavior proposed, although partially supported by experimental results, differs from more geometrical approaches based on explicit 4D measures and trajectory estimation in that it is based on direct visual information, such as stereo disparity or the 2D image motion field. The experiment is limited to analysis of the optical flow information extracted from manipulative actions performed by a human operator. These experiments demonstrate that the qualitative approach proposed is not in contrast with human behavior and that the two-arm manipulation task proposed can be seen as a testbed for qualitative and geometrical approaches.>

One way to control the mechanical interactions between a manipulator and its environment is by specifying the manipulator's end-point impedance. According to this view, the function of a controller is to determine the force that the controlled system should apply in response to an externally imposed state, i.e., to determine an output force field. The possibility of combining the output force fields generated by a number of separate controllers in order to approximate an arbitrary output field is considered for a kinematically redundant manipulator. The end-point force fields of a simulated kinematically redundant manipulator operated by a set of spring-link actuators is numerically derived. The results indicate that the linear superposition of end-point fields may provide a quite good approximation of the actual passive behavior. This offers a simple way for solving the ill-posed problems associated with the specification of end-point impedance fields in a kinematically redundant system.

One of the main problems in robotic research is planning. Different approaches have been considered, ranging from global to local planning. In the authors' approach, the key idea is that of planning movements of redundant robots, which involves both robotic and AI aspects. Pushing is used as a case study and sensorial feedback is considered in order to provide the planner with updated information on the dynamic evolution of the scene and to be able to deal with a priori unknown objects.>

Present a perspective in relation to the use of vision for the control of robots and for the monitoring of robot actions. In order to explain the approach some experiments have been performed in the field of object manipulation and robot navigation. In particular the monitoring of pushing and tapping actions by means of dynamic measurements performed on image sequences are reported. The experiments show that, not only it seems possible to detect unexpected events, but it is possible to control the arm or vehicle trajectory in such a way to achieve a complex task like the pushing of an unknown object along a predetermined trajectory.>