Tri-Modal Speed and Separation Monitoring Technique using Static-Dynamic Danger Field Implementation

摘要

Speed and Separation Monitoring (SSM) has become one of the recent methods to ensure safety in Human Robot Interactions (HRI). SSM maintains a safe separation distance between the robot and any human collaborator and issues a safety-rated halt to the robot when the set safe distance is violated. SSM could be classified into two: Static, which uses a predefined offline safeguard volume and Dynamic, which uses a more-fit online-calculated volume. A trade-off arises between the two as Static SSM is often over conservative and significantly affect the productivity of the system, while dynamic SSM may become less reliable in terms of safety performance as the maximum velocity of the robot is increased. These trends are confirmed through the system created in this study. To overcome the trade-off, this study proposes a combination of the two in a tri-modal SSM. Using the KUKA Robot AGILUS SIXX as arm manipulator, Microsoft Kinect as sensor, JOpenShowVar as middleware, and MATLAB R2013a for the user interface, the researchers were able to create a system that offers a better trade-off compared to its counterparts. The proposed system is reliably safe at higher speeds compared to the dynamic implementation but still significantly productive compared to the static implementation.