Strategies for Improving and Evaluating Robot Registration Performance.

Abstract

In a dynamic robotic workcell environment where robots may be frequently relocated or may need to collaborate with other robots, it is simpler and more robust to program robots in an external or unifying reference frame. The process of robot registration involves finding the location of a robot with respect to another reference frame. For instance, if parts are in known locations on a table and a robot can locate itself with respect to the table (an external reference frame), then the robot will also know the location of the parts. Furthermore, if two or more robots can locate themselves with respect to the table, then each robot will not only know the location of the parts, but also the location of every other robot. This knowledge facilitates the coordination of robot motions and robot collaboration and eases the integration of additional robots into the workcell. Since robot registration is critically necessary and occurs frequently, its process needs to be inexpensive, fast, and accurate. This paper details the requirements for a relatively inexpensive and fast robot registration experience, along with detailing strategies that incur significant improvements to registered robot positioning accuracy with minimal overhead. A quantitative verification process is presented to evaluate the performance impacts of these strategies. Peg-in-hole experiments are conducted to validate the notion that more accurate robot registration translates to more reliable task-level performance.