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arXiv · 2411.01387

Wallbounce : Push wall to navigate with Contact-Implicit MPC

Xiaohan Liu·Cunxi Dai·John Z. Zhang·Arun Bishop·Zachary Manchester·Ralph Hollis
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Abstract

In this work, we introduce a framework that enables highly maneuverable locomotion using non-periodic contacts. This task is challenging for traditional optimization and planning methods to handle due to difficulties in specifying contact mode sequences in real-time. To address this, we use a bi-level contact-implicit planner and hybrid model predictive controller to draft and execute a motion plan. We investigate how this method allows us to plan arm contact events on the shmoobot, a smaller ballbot, which uses an inverse mouse-ball drive to achieve dynamic balancing with a low number of actuators. Through multiple experiments we show how the arms allow for acceleration, deceleration and dynamic obstacle avoidance that are not achievable with the mouse-ball drive alone. This demonstrates how a holistic approach to locomotion can increase the control authority of unique robot morpohologies without additional hardware by leveraging robot arms that are typically used only for manipulation. Project website: https://cmushmoobot.github.io/Wallbounce

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Xiaohan Liu, Cunxi Dai, John Z. Zhang, Arun Bishop, Zachary Manchester, Ralph Hollis. 2024-11-03. Wallbounce : Push wall to navigate with Contact-Implicit MPC. https://arxiv.org/abs/2411.01387

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