Miller Andrew T. author Columbia University. Computer Science Knoop Steffen author Christensen Henrik Iskov author Allen Peter K. author Columbia University. Computer Science Columbia University. Computer Science originator text Articles 2003 English Automatic grasp planning for robotic hands is a difficult problem because of the huge number of possible hand configurations. However, humans simplify the problem by choosing an appropriate prehensile posture appropriate for the object and task to be performed. By modeling an object as a set of shape primitives, such as spheres, cylinders, cones and boxes, we can use a set of rules to generate a set of grasp starting positions and pregrasp shapes that can then be tested on the object model. Each grasp is tested and evaluated within our grasping simulator "GraspIt!", and the best grasps are presented to the user. The simulator can also plan grasps in a complex environment involving obstacles and the reachability constraints of a robot arm. Robotics Piscataway, N.J. IEEE 2003 1824 1829 http://dx.doi.org/10.1109/ROBOT.2003.1241860