This work addresses the problem of planning the reach-to-grasp trajectory for a robotic arm and hand, when there is uncertainty in the pose of the object being grasped. If the object is not in its expected location, then the robot may still gain additional information about the object pose by making tactile or haptic observations if a finger or other part of the hand collides with part of the object during the reach-to-grasp operation. Therefore, it is desirable to plan the r

This work, firstly, describes how to iteratively update localisation knowledge using tactile observations from a previous grasp attempt; secondly, shows how successive grasp trajectories can be planned with respect to these iteratively refined object poses; and, thirdly, shows how each reach-to-grasp trajectory can be deliberately planned to maximise new tactile information gain, while also reaching towards the expected grasp location derived from previous information. #Robot

Planning in robotics means coping with dynamic and uncertain worlds. Unstructured worlds are perceived by the agent through noisy sensors as laser, camera and so on. Especially, when the agent works "in contact" with the environment, uncertainty plays a crucial role. In such cases, the agent interacts actively with the surrounding environment and its actions affect future states of the environment itself. In other words, future observations are affected by earlier agent's act