Global estimation of an object’s pose using tactile sensing

It is essential for a successful completion of a robot object grasping and manipulation task to accurately sense the manipulated object’s pose. Typically, computer vision is used to obtain this information, but it may not be available or be reliable in certain situations. This paper presents a global optimisation method where tactile and force sensing together with the robot’s proprioceptive data are used to find an object’s pose. This method is used to either improve an estimate of the object’s pose given by vision or globally estimating it when no vision is available. Results show that the proposed method consistently improves an initial estimate (e.g. from vision) and is also able to find the object’s pose without any prior estimate. To demonstrate the performance of the algorithm, an experiment is carried out where the robot is handed a small object (a pencil) and inserts it into a narrow hole without any use of vision.