We present an approach to safe physical Human-Robot Interaction (pHRI) for industrial robots, including collision detection, distinguishing accidental from intentional contacts, and achieving collaborative tasks. Typical industrial robots have a closed control architecture that accepts only velocity/position reference inputs, there are no joint torque sensors, and little or no information is available to the user on robot dynamics and on low-level joint controllers. Nonetheless, taking also advantage of the presence of a Force/Torque (F/T) sensor at the end-effector, a safe pHRI strategy based on kinematic information, on measurements from joint encoders and motor currents, and on end-effector forces/torques can be realized. An admittance control law has been implemented for collaboration in manual guidance mode, with whole-body collision detection in place both when the robot is in autonomous operation and when is simultaneously collaborating with a human. Several pHRI experiments validate the approach on a KUKA KR5 Sixx R650 robot equipped with an ATI F/T sensor.

In this paper we present a real-time collision check algorithm based on the parallel computation capabilities of recent graphics card's GPUs. We show an effective application of the proposed algorithm to solve the task-constrained real-time motion planning problem for a redundant manipulator. We propose a proof-of-concept motion planner based on fast collision check of predicted robot motion over a given planning horizon. Obstacles are avoided exploiting the redundancy of the robot. Reactive velocities are computed for some control points placed on the robot and projected in the null space of the task Jacobian. The approach is validated through simulations in V-Rep environments and experiments on the KUKA LWR-IV 7-DoF manipulator.

We present further computational tools and control results in the framework of human-robot coexistence and collaboration. A GPU parallel processing algorithm is introduced for real-time monitoring of dynamic distances between a robot and generic obstacles moving in its environment, taking advantage of the handling of RGB-D data directly in the depth space of the sensor. Combined with the use of model-based residual signals, this approach allows efficient detection of contact points on the robot with simultaneous estimation of the exchanged contact forces. When the robot is kinematically redundant for the original task and undergoes a physical contact, a control scheme accommodates collaboration trying to preserve task execution, or reacts by abandoning the task if the estimated contact forces exceed some safety threshold. Experimental results are reported for a KUKA LWR.

During human-robot collaboration tasks, we may physically touch the robot at a generic location and engage an intentional exchange of forces while realizing coordinated motion of the common contact point. In order to control the relative motion and the exchanged contact forces, the latter need to be estimated without using any local force sensing device. Building upon our recent works, we generalize the classical hybrid force/velocity control design to this situation, handling complementary quantities along the directions of a suitable contact task frame in a dynamically decoupled way. The contact force is estimated online using our residual method together with an external sensor to localize the contact point, and the time-varying contact task frame is obtained analytically from this estimate. Experimental results are presented for a KUKA LWR4 robot using a Kinect sensor.

During human-robot interaction tasks, a human may physically touch a robot and engage in a collaboration phase with exchange of contact forces and/or requiring coordinated motion of a common contact point. Under the premise of keeping the interaction safe, the robot controller should impose a desired motion/force behavior at the contact or explicitly regulate the contact forces. Since intentional contacts may occur anywhere along the robot structure, the ability of controlling generalized contact motion and force becomes an essential robot feature. In our recent work, we have shown how to estimate contact forces without an explicit force sensing device, relying on residual signals to detect contact and on the use of an external (depth) sensor to localize the contact point. Based on this result, we introduce two control schemes that generalize the impedance and direct force control paradigms to a generic contact location on the robot, making use of the estimated contact forces. The issue of human-robot task compatibility is pointed out in case of control of generalized contact forces. Experimental results are presented for a KUKA LWR robot using a Kinect sensor.

Physical human-robot collaboration is characterized by a suitable exchange of contact forces between human and robot, which can occur in general at any point along the robot structure. If the contact location and the exchanged forces were known in real time, a safe and controlled collaboration could be established. We present a novel approach that allows localizing the contact between a robot and human parts with a depth camera, while determining in parallel the joint torques generated by the physical interaction using the so-called residual method. The combination of such exteroceptive sensing and model-based techniques is sufficient, under suitable conditions, for a reliable estimation of the actual exchanged force at the contact, realizing thus a virtual force sensor. Multiple contacts can be handled as well. We validate quantitatively the proposed estimation method with a number of static experiments on a KUKA LWR. An illustration of the use of estimated contact forces in the realization of collaborative behaviors is given, reporting preliminary experiments on a generalized admittance control scheme at the contact point.