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Industrial robots are increasingly deployed in applications requiring an endeffector tool to closely track a specified path, such as in spraying andwelding. Performance and productivity present possibly conflicting objectives:tracking accuracy, path speed, and motion uniformity. Industrial robots areprogrammed through motion primitives consisting of waypoints connected bypre-defined motion segments, with specified parameters such as path speed andblending zone. The actual executed robot motion depends on the robot jointservo controller and joint motion constraints (velocity, acceleration, etc.)which are largely unknown to the users. Programming a robot to achieve thedesired performance today is time-consuming and mostly manual, requiring tuninga large number of coupled parameters in the motion primitives. The performancealso depends on the choice of additional parameters: possible redundant degreesof freedom, location of the target curve, and the robot configuration. Thispaper presents a systematic approach to optimize the robot motion primitivesfor performance. The approach first selects the static parameters, then themotion primitives, and finally iteratively update the waypoints to minimize thetracking error. The ultimate performance objective is to maximize the pathspeed subject to the tracking accuracy and speed uniformity constraints overthe entire path. We have demonstrated the effectiveness of this approach insimulation for ABB and FANUC robots for two challenging example curves, andexperimentally for an ABB robot. Comparing with the baseline using the currentindustry practice, the optimized performance shows over 200% performanceimprovement.

High-Speed High-Accuracy Spatial Curve Tracking Using Motion Primitives in Industrial Robots