Ciocarlie Matei author Columbia University. Computer Science Goldfeder Corey author Columbia University. Computer Science Allen Peter K. author Columbia University. Computer Science Columbia University. Computer Science originator text Articles 2007 English In this paper, we build upon recent advances in neuroscience research which have shown that control of the human hand during grasping is dominated by movement in a configuration space of highly reduced dimensionality. We extend this concept to robotic hands and show how a similar dimensionality reduction can be defined for a number of different hand models. This framework can be used to derive planning algorithms that produce stable grasps even for highly complex hand designs. Furthermore, it offers a unified approach for controlling different hands, even if the kinematic structures of the models are significantly different. We illustrate these concepts by building a comprehensive grasp planner that can be used on a large variety of robotic hands under various constraints. Robotics Piscataway, N.J. IEEE 2007 3270 3275 http://dx.doi.org/10.1109/IROS.2007.4399227