Simultaneous Stiffness and Trajectory Optimization for Energy Minimization of Pick-and-Place Tasks of Sea-Actuated Parallel Robots

Abstract

Abstract A major field of industrial robot applications deals with repetitive tasks that alternate between operating points. For these so-called pick-and-place operations, parallel kinematic manipulators (PKM) are frequently employed. These tasks tend to automatically run for a long period of time and therefore minimizing energy consumption is always of interest. The latest developments addressing this issue deal with the use of elastic elements and actuators, where research on series elastic actuators (SEA) appears underrepresented. Motivated by a simplified introductory thought experiment, this paper explores the possibilities of minimizing energy consumption of PKM actuated by SEA during pick-and-place tasks. The idea is to excite eigenmotions that result from the actuator springs and exploit their oscillating characteristics. To this end, a typical cyclic pick-and-place operation is analyzed and a dynamic model of SEA driven PKM is derived. Subsequently, an energy minimizing optimal control problem is formulated where operating trajectories as well as SEA stiffnesses are optimized simultaneously. Here, optimizing the actuator stiffness does not account for variable stiffness actuators. It serves as a tool for the design and sizing process. The hypothesis on energy reduction is tested on two (parallel) robot applications where redundant actuation is also addressed. Lastly, results are shown and the validity of this approach is discussed.