Catch the Ball: Accurate High-Speed Motions for Mobile Manipulators via Inverse Dynamics Learning

Understand

Mobile manipulators consist of a mobile platform equipped with one or more robot arms and are of interest for a wide array of challenging tasks because of their extended workspace and dexterity.

• Typically, mobile manipulators are deployed in slow-motion collaborative robot scenarios.
• In this paper, we consider scenarios where accurate high-speed motions are required.
• We introduce a framework for this regime of tasks including two main components: (i) a bi-level motion optimization algorithm for real-time trajectory generation, which relies on Sequential Quadratic Programming (SQP) and Quadratic Programming (QP), respectively; and (ii) a learning-based controller optimized for precise tracking of high-speed motions via a learned inverse dynamics model.