Abstract:

This paper studies a manipulator co-design problem of motors and motions for multiple tasks. To reduce computational burden and improve scalability as the number of tasks grows, this paper introduces a distributed co-design framework to handle the co-design process for all tasks in a distributed fashion. Moreover, this paper presents a distributed constrained optimization algorithm, which secures a unified set of design parameters for all tasks ultimately such that the total average of motor operation efficiency is optimized and the design constraints are satisfied across all tasks and motors. The distributed manner reduces the computational load by allowing each agent to solve co-design optimization solely for its designated task. A numerical simulation further verifies the proposed algorithm.