Obstacle Avoidance using a Capacitive Skin for Safe HumanRobot Interaction. The paper describes a control framework using a capacitive skin for advanced and safe humanrobot interactions. The skin consists of high density capacitive sensors which are able to detect objects at close distance. We propose a multitask kinematic control scheme which manages at once the control task of the endeffector and the obstacle avoidance task by using the capacitive skin measurements. To solve the multiobjective problem, a WeightPrioritized solution based on a QP formalism is adopted. The robustness of the kinematic controller is enhanced by adding a local joint reconfiguration when the robot moves close to a singularity. Experimental results on manipulator arm equipped with the capacitive sensors are presented in realistic situations of humanrobot interactions.

With Proximity Servoing towards Safe HumanRobotInteraction In this paper, we present a serial kinematic robot manipulator equipped with multimodal proximity sensing modules not only on the TCP but distributed on the robotxe2x80x99s surface. The combination of close distance proximity information from capacitive and timeofflight (ToF) measurements allows the robot to perform safe reflexlike and collisionfree motions in a changing environment, e.g. where humans and robots share the same workspace. Our methods rely on proximity data and combine different strategies to calculate orthogonal avoidance motions. These motions are instantaneous optimal and are fed directly into the motion controller (proximity servoing). The strategies are prioritized, firstly to avoid collision and then secondly to maintain the task motion if kinematic redundancy is available. The motion is then optimized for avoidance, best manipulability, and smallest endeffector velocity deviation. We compare our methods with common force field based methods.