Imagine that you are reaching into the fridge to grasp an object you can only partially see. Rather than relying solely on vision, you must use touch in order to localise it and securely grasp it. However, humans would not poke the object to localise it first and then grasp it. We compensate for the uncertainty by approaching the object in a way such that if a contact occurs it will generate enough information about where the object is and the object will be grasped with a mi

Imagine that you are reaching into the fridge to grasp an object you can only partially see. Rather than relying solely on vision, you must use touch in order to localise it and securely grasp it. However, humans would not poke the object to localise it first and then grasp it. We compensate for the uncertainty by approaching the object in a way such that if a contact occurs it will generate enough information about where the object is and the object will be grasped with a mi

Link to video: https://www.youtube.com/watch?time_continue=3&v=5Fuhk4oKIvY Human robot collaboration on the shop floor presents a significant set of challenges. In this project we have developed methods for enabling a shop floor mobile robot to assist a human in logistical and assembly tasks, by bringing tools, parts and assisting in the assembly process to reduce the strain on the human worker. The scenario is as follows. In structure assembly, equipment installation and fin

Successful grasp planning requires an appropriate finger placement for which object geometry and location need to be known. Here we investigate how position uncertainty and shape influence the selection of a two-finger pinch grasp. Elliptical cylinders were stereoscopically presented in rapid succession. The position of each cylinder was randomly selected using two orthogonal Gaussian distribution whose orientation changed at each trial. The axes of the elliptical base were a

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

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