Manipulator Grasping and Pushing Operations

The primary goal of this research is to develop theoretical tools for analysis, synthesis, application of primitive manipulator operations. The primary method is to extend and apply traditional tools of classical mechanics. The results are of such a general nature that they address many different aspects of industrial robotics, including effector and sensor design, planning and programming tools and design of auxiliary equipment. Some of the manipulator operations studied are: (1) Grasping an object. The object will usually slide and rotate during the period between first contact and prehension. (2) Placing an object. The object may slip slightly in the fingers upon contact with the table as the base aligns with the table. (3) Pushing. Often the final stage of mating two parts involves pushing one object into the other.

Biologically Plausible Neural Circuits for Realization of Maximum Operations

Object recognition in the visual cortex is based on a hierarchical architecture, in which specialized brain regions along the ventral pathway extract object features of increasing levels of complexity, accompanied by greater invariance in stimulus size, position, and orientation. Recent theoretical studies postulate a non-linear pooling function, such as the maximum (MAX) operation could be fundamental in achieving such invariance. In this paper, we are concerned with neurally plausible mechanisms that may be involved in realizing the MAX operation. Four canonical circuits are proposed, each based on neural mechanisms that have been previously discussed in the context of cortical processing. Through simulations and mathematical analysis, we examine the relative performance and robustness of these mechanisms. We derive experimentally verifiable predictions for each circuit and discuss their respective physiological considerations.