In studying grasping and manipulation we find two very different approaches to the subject: knowledge-based approaches based primarily on empirical studies of human grasping and manipulation, and analytical approaches based primarily on physical models of the manipulation process. This chapter begins with a review of studies of human grasping, in particular our development of a grasp taxonomy and an expert system for predicting human grasp choice. These studies show how object geometry and task requirements (as well as hand capabilities and tactile sensing) combine to dictate grasp choice. We then consider analytic models of grasping and manipulation with robotic hands. To keep the mathematics tractable, these models require numerous simplifications which restrict their generality. Despite their differences, the two approaches can be correlated. This provides insight into why people grasp and manipulate objects as they do, and suggests different approaches for robotic grasp and manipulation planning. The results also bear upon such issues such as object representation and hand design.

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Authors and Affiliations

1. Design Division, Mechanical Engineering Department, Stanford University, Stanford, CA, 94305, USA

   Mark R. Cutkosky & Robert D. Howe

Editors and Affiliations

1. Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, CA, 91109, USA

   Subramanian T. Venkataraman

2. Center for Neural Engineering, Department of Computer Science, University of Southern California, Los Angeles, CA, 90089, USA

   Thea Iberall

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