Force control synthesis for task-space controlled industrial robots
Vendor-neutral, transferable robot skills for flexible production systems
To program flexible production systems, skillbased robot programming utilizes the abstraction of skills. Skills encapsulate robotic capabilities and can be composed to complex robot applications. Skill-based robot applications are vendor-neutral. However, generalized skills are prone to conservative control performances due to unmodeled dynamic behavior. A systematic control synthesis is the missing step towards vendor-neutral, transferable robot skills for flexible production systems. In this work an almost time-optimal control approach SVSC is applied to the task function approach iTaSC. An identified task-space state-space system model is used for control synthesis. The synthesis results from the solution of a convex optimization problem. Different syntheses are compared and evaluated for robot force control. This research contributes by addressing control synthesis in task-space approaches and experimental evaluation of SVSC within the domain of robot control.