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In this paper, we propose physically meaningful energy related safety indicators for robots sharing their workspace with humans. Based on these indicators, safety criteria are introduced as constraints in the control algorithm. The first constraint is placed on the kinetic energy of the robotic system to limit the amount of dissipated energy in case of collision. This constraint depends on the distance between the robot and the human operator. The distance is computed with a point cloud based algorithm acquired using a set of depth sensors (Kinects). The second constraint is on the amount of potential energy that is allowed to be generated within the human-robot system during physical contact. It is used to modulate the contact forces. The control algorithm is formulated as an optimization problem and computes every time step the actuation torques for a KUKA LWR4 manipulator given some task to be performed, the introduced constraints and the physical limitations of the system to respect. The overall framework allows a human operator to safely enter the robot's workspace and physically interact with it.

In this paper, we propose a physically meaningful energy-related safety indicator for robots sharing their workspace with humans. Based on this indicator, a safety criterion accounting for the breaking capabilities of the robot is included as a quadratic constraint in the control algorithm. This constraint is modulated by the distance between the human operator and the end-effector of the robot. The control algorithm is formulated as an optimization problem and computes the actuation torque of a robotic manipulator given some task to be performed and physical constraints to respect. The overall framework is validated in a physics simulation software on a Kuka LWR4 and different behaviours of the robot towards a considered obstacle in its environment are evaluated and discussed.

Widely used for surface slopes measurements and for three-dimensional shape reconstruction, deflectometry is a particularly powerful technique that can also be applied for defects detection on specular surfaces. In the visible domain, deflectometry is usually based on the projection of complex encoded light patterns and necessitates heavy processing that makes it not suitable for inline inspection. In this paper, A new deflectometry based approach that is more adapted for inline inspection of linearly moving parts (parts on conveyors) is proposed. Based on a more affordable and a simpler hardware setup, the new approach allows at the same time for a proper localization and a precise geometrical quantification of any defects on the scanned specular surfaces. The proposed approach uses a fast and simple processing algorithm that lends itself very well to real-time inspection. The new method is tested and validated in laboratory for the inspection of defects on specular surfaces of plastic parts.

SUMMARYLegged robots have the potential to navigate in more challenging terrains than wheeled robots. Unfortunately, their control is more demanding, because they have to deal with the common tasks of mapping and path planning as well as more specific issues of legged locomotion, like balancing and foothold planning. In this paper, we present the integration and the development of a stabilized vision system on the fully torque-controlled hydraulically actuated quadruped robot (HyQ). The active head added onto the robot is composed of a fast pan and tilt unit (PTU) and a high-resolution wide angle stereo camera. The PTU enables camera gaze shifting to a specific area in the environment (both to extend and refine the map) or to track an object while navigating. Moreover, as the quadruped locomotion induces strong regular vibrations, impacts or slippages on rough terrain, we took advantage of the PTU to mechanically compensate for the robot's motions. In this paper, we demonstrate the influence of legged locomotion on the quality of the visual data stream by providing a detailed study of HyQ's motions, which are compared against a rough terrain wheeled robot of the same size. Our proposed Inertial Measurement Unit (IMU)-based controller allows us to decouple the camera from the robot motions. We show through experiments that, by stabilizing the image feedback, we can improve the onboard vision-based processes of tracking and mapping. In particular, during the outdoor tests on the quadruped robot, the use of our camera stabilization system improved the accuracy on the 3D maps by 25%, with a decrease of 50% of mapping failures.