Active tactile object exploration with Gaussian processesZhengkun Yi; Roberto Calandra; Filipe Veiga; Herke van Hoof; Tucker Hermans; Yilei Zhang; Jan Peters
In: 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-2016), October 9-14, Daejeon, Korea, Democratic People's Republic of, Pages 4925-4930, IEEE, 2016.
Accurate object shape knowledge provides important information for performing stable grasping and dexterous manipulation. When modeling an object using tactile sensors, touching the object surface at a fixed grid of points can be sample inefficient. In this paper, we present an active touch strategy to efficiently reduce the surface geometry uncertainty by leveraging a probabilistic representation of object surface. In particular, we model the object surface using a Gaussian process and use the associated uncertainty information to efficiently determine the next point to explore. We validate the resulting method for tactile object surface modeling using a real robot to reconstruct multiple, complex object surfaces.