Towards Haptic-Based Dual-Arm Manipulation.

Vision is the main component of current robotics systems that is used for manipulating objects. However, solely relying on vision for hand-object pose tracking faces challenges such as occlusions and objects moving out of view during robotic manipulation. In this work, we show that object kinematics can be inferred from local haptic feedback at the robot-object contact points, combined with robot kinematics information given an initial vision estimate of the object pose. A planar, dual-arm, teleoperated robotic setup was built to manipulate an object with hands shaped like circular discs. The robot hands were built with rubber cladding to allow for rolling contact without slipping. During stable grasping by the dual arm robot, under quasi-static conditions, the surface of the robot hand and object at the contact interface is defined by local geometric constraints. This allows one to define a relation between object orientation and robot hand orientation. With rolling contact, the displacement of the contact point on the object surface and the hand surface must be equal and opposite. This information, coupled with robot kinematics, allows one to compute the displacement of the object from its initial location. The mathematical formulation of the geometric constraints between robot hand and object is detailed. This is followed by the methodology in acquiring data from experiments to compute object kinematics. The sensors used in the experiments, along with calibration procedures, are presented before computing the object kinematics from recorded haptic feedback. Results comparing object kinematics obtained purely from vision and from haptics are presented to validate our method, along with the future ideas for perception via haptic manipulation.