Adaptive Collision Sensitivity for Efficient and Safe Human-Robot Collaboration

TL;DR

An increase in productivity over 45% is shown from using the standard approach that interrupts the tasks during every collision, while reducing the cycle time and the number of interruptions, and ensures the safety of human operators.

Abstract

What is considered safe for a robot operator during physical human-robot collaboration (HRC) is specified in corresponding HRC standards (e.g., ISO/TS 15066). The regime that allows collisions between the moving robot and the operator, called Power and Force Limiting (PFL), restricts the permissible contact forces. Using the same fixed contact thresholds on the entire robot surface results in significant and unnecessary productivity losses, as the robot needs to stop even when impact forces are within limits. Here we present a framework that decides whether the robot should interrupt or continue its motion based on estimated collision force computed individually for different parts of the robot body and dynamically on the fly, based on the effective mass of each robot link and the link velocity. We performed experiments on simulated and real 6-axis collaborative robot arm (UR10e) with sensitive skin (AIRSKIN) for collision detection and isolation. To demonstrate the generality of our method, we added experiments on the simulated KUKA LBR iiwa robot, where collision detection and isolation draws on joint torque sensing. On a mock pick-and-place scenario with both transient and quasi-static collisions, we demonstrate how sensitivity to collisions influences the task performance and number of stops. We show an increase in productivity over 45% from using the standard approach that interrupts the tasks during every collision. While reducing the cycle time and the number of interruptions, our framework also ensures the safety of human operators. The method is applicable to any robot for which the effective mass can be calculated.

Figures (7)

• Figure 1: Schematic overview of the algorithm deployed on the UR10e robot with AIRSKIN (Left) and KUKA LBR iiwa 7 (Right). (Top) The colored parts of the robots are used for collisions in our experiments---the colors are used just for illustration and to relate robot links to collision locations in the workspace. (Bottom) The colored circles correspond to colors of the links. The color bars show the collision reaction changes over time (red = stop; green = continue) during the movements in a given axis (see \ref{['sec:task']}), and end with a collision with given objects. The length of bars is proportional to the length of the movement in the given axis. The two mentioned methods (FIXED MASS and ADAPTIVE MASS) both calculate the collision reactions in real time during the movements. FIXED MASS uses a fixed mass value for each link and ADAPTIVE MASS calculates also effective mass based on the current configuration---see \ref{['sec:threshold_policies']}.
• Figure 2: Schematic overview of collision handling pipeline adapted from haddadin2017robot. See text for details.
• Figure 3: The environment used in the experiments. The hanging buckets simulate transient contacts. The impact measuring device fixed on a table simulates quasi-static contact (clamping scenario).
• Figure 4: ef and hmm for three skin parts in every configuration of the performed task for the UR10e robot. Colors correspond to colors in \ref{['fig:heatmaps']}.
• Figure 5: Results -- UR10e with AIRSKIN. (Left) Simulation. (Right) Real robot.