No abstract

In order to enable efficient control of a humanhumanoid in physical contact settings, a real-time solution for a contact observer is required. We propose a novel approach for proprioceptive sensor based contact sensing suitable for affordable personal robots with no force/torque or electric current sensing. We combine robot model knowledge and the output of acceleration resolved quadratic programming wholebody controller to make a prediction of expected position tracking error for computing our proposed contact observer signal. We demonstrate the efficiency of our approach in the experiments of contact detection and estimation of collision direction and intensity on a real humanoid robot Pepper platform controlled by a task-space multi-objective quadratic programming controller.

Robotic manipulation tasks require the knowledge on the configuration of the object in use. Since most objects are generally not equipped with any sensor, an estimator is required. Furthermore, if an object is articulated, i.e. includes passive joints, the estimation process has to reconstruct the pose of the object floating base and its joints variables, concurrently with the manipulation control. We address the estimation problem with an online virtual visual servoing paradigm written as a quadratic program. Our estimator is integrated in closed-loop with the manipulation control governing the robot, which is also a quadratic program. Tracking and manipulation experiments, using a humanoid, show the effectiveness of our approach.