Extended Calculation of the Dynamic Separation Distance for Robot Speed Adaption in the HumanRobot Interaction Speed and separation monitoring (SSM) is one of the four permitted collaborative operations in humanrobot interaction (HRI). Current standards and guidelines provide users and system integrators with a simple basis to calculate permissible separation distances between human workers and robots. However, high impact factors due to various simplifications result in oversized safety zones, which in practice often leads to difficulties in layout and process design. The very large safety zones that have been required so far are one of the existing obstacles to the implementation of HRI applications, especially in SSM. This paper describes extension approaches to determine the dynamic separation distance more precisely and to calculate the adapted robot speed. The developed methods are integrated into an existing HRI simulation tool based on the Robot Operating System (ROS) and finally analyzed. Taking into account the normative conditions, the implemented methods enable users and system integrators to simulate, analyze and optimize HRI scenarios already in the planning phase.

Safe physical HRI: Toward a unified treatment of speed and separation monitoring together with power and force limiting Socalled collaborative robots are a current trend in industrial robotics. However, they still face many problems in practical application such as reduced speed to ascertain their collaborativeness. The standards prescribe two regimes: (i) speed and separation monitoring and (ii) power and force limiting, where the former requires reliable estimation of distances between the robot and human body parts and the latter imposes constraints on the energy absorbed during collisions prior to robot stopping. Following the standards, we deploy the two collaborative regimes in a single application and study the performance in a mock collaborative task under the individual regimes, including transitions between them. Additionally, we compare the performance under xe2x80x9csafety zone monitoringxe2x80x9d with keypoint pairwise separation distance assessment relying on an RGBD sensor and skeleton extraction algorithm to track human body parts in the workspace. Best performance has been achieved in the following setting: robot operates at full speed until a distance threshold between any robot and human body part is crossed; then, reduced robot speed per power and force limiting is triggered. Robot is halted only when the operatorxe2x80x99s head crosses a predefined distance from selected robot parts. We demonstrate our methodology on a setup combining a KUICA LBR iiwa robot, Intel RealSense RGBD sensor and OpenPose for human pose estimation.