A Combined Learning and Optimization Framework to Transfer Human Whole-body Loco-manipulation Skills to Mobile Manipulators

Jianzhuang Zhao; Francesco Tassi; Yanlong Huang; Elena De Momi; Arash Ajoudani

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arXiv · 2402.13915

A Combined Learning and Optimization Framework to Transfer Human Whole-body Loco-manipulation Skills to Mobile Manipulators

Jianzhuang Zhao·Francesco Tassi·Yanlong Huang·Elena De Momi·Arash Ajoudani

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Abstract

Humans' ability to smoothly switch between locomotion and manipulation is a remarkable feature of sensorimotor coordination. Leaning and replication of such human-like strategies can lead to the development of more sophisticated robots capable of performing complex whole-body tasks in real-world environments. To this end, this paper proposes a combined learning and optimization framework for transferring human's loco-manipulation soft-switching skills to mobile manipulators. The methodology departs from data collection of human demonstrations for a locomotion-integrated manipulation task through a vision system. Next, the wrist and pelvis motions are mapped to mobile manipulators' End-Effector (EE) and mobile base. A kernelized movement primitive algorithm learns the wrist and pelvis trajectories and generalizes to new desired points according to task requirements. Next, the reference trajectories are sent to a hierarchical quadratic programming controller, where the EE and the mobile base reference trajectories are provided as the first and second priority tasks, generating the feasible and optimal joint level commands. A locomotion-integrated pick-and-place task is executed to validate the proposed approach. After a human demonstrates the task, a mobile manipulator executes the task with the same and new settings, grasping a bottle at non-zero velocity. The results showed that the proposed approach successfully transfers the human loco-manipulation skills to mobile manipulators, even with different geometry.

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Jianzhuang Zhao, Francesco Tassi, Yanlong Huang, Elena De Momi, Arash Ajoudani. 2024-02-21. A Combined Learning and Optimization Framework to Transfer Human Whole-body Loco-manipulation Skills to Mobile Manipulators. https://arxiv.org/abs/2402.13915

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