Grasp Algorithms for Optotactile Robotic Sample Acquistion
Robotic sample acquisition is basically grasping. Multi-finger robot sample grasping devices are controlled to securely pick up samples. While optimal grasps for perfectly modeled objects are known, grasping unmodeled objects, like a surface sample, is an open research problem. A major source of difficulty in robotic grasping, therefore, is the sensing of object parameters and grasp quality. Humans combine the high information content of vision, several types of haptic/tactile sensors in the fingers, and a sophisticated learning process to grasp unknown objects. In comparison, current robotic graspers rely on a much more limited set of sensors, particularly for measuring tactile properties.