Session: MR-03-01 - Compliant Mechanisms (A. Midha Symposium)

Paper Number: 91310

91310 - A Variable Stiffness End-of-Arm Mechanism for Safe Operation in Industrial Environments 

In robotic manipulation, uncertainties in the operating environment can result in the exchange of unintended forces that can harm either the operator, robot, tool, or the operating environment. In this study, we present a variable stiffness end-of-arm mechanism (VSEAM) to improve the collision safety of industrial robots. In VSEAM, the endpoint stiffness of the robotic manipulator is controlled using the displacement of permanent magnets. Additionally, a calibrated force model is developed for these magnets to detect external collisions. In the event of an unintended collision, the nonlinear compliance of the VSEAM provides passive displacement of the tool and provides enough time for the robot to react to the collision. Such passive displacement helps in absorbing the partial impact energy and thus protects the tool and the environment from damage. We validated the mechanism during unintended collisions at two different robot speeds i.e. end-effector velocities 0.3 m/s, and 0.5 m/s, and repeated the experiments for two different tool masses, 0.4 kg, and 1 kg. We then compared the transmitted forces in low and medium stiffness settings of the VSEAM to the high stiffness setting of the robot (in the absence of the VSEAM). Through the experimental results, we demonstrate that the VSEAM can reduce the transmitted forces by approx. 50%.

Presenting Author: Ehsan Tarkesh Esfahani University at Buffalo

Presenting Author Biography: Ehsan Tarkesh Esfahani received an M.S. degree in electrical engineering and a Ph.D. degree in mechanical engineering from the University of California Riverside, Riverside, CA, USA, in 2012. He is currently an Associate Professor with the Department of Mechanical and Aerospace Engineering, University at Buffalo, SUNY, Buffalo, NY, USA. His research interests include Human-Machine Interaction, Brain-Computer Interfaces, Medical Robotics, Neuroergonomics, Human-In-the loop systems, Swarm tactics, and Reinforcement learning.

Authors:

Sri Sadhan Jujjavarapu University at Buffalo
Ehsan Tarkesh Esfahani University at Buffalo