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Computer Science > Robotics

arXiv:2303.13726 (cs)
[Submitted on 24 Mar 2023 (v1), last revised 29 Jul 2023 (this version, v2)]

Title:Topology-Based MPC for Automatic Footstep Placement and Contact Surface Selection

Authors:Jaehyun Shim, Carlos Mastalli, Thomas Corbères, Steve Tonneau, Vladimir Ivan, Sethu Vijayakumar
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Abstract:State-of-the-art approaches to footstep planning assume reduced-order dynamics when solving the combinatorial problem of selecting contact surfaces in real time. However, in exchange for computational efficiency, these approaches ignore joint torque limits and limb dynamics. In this work, we address these limitations by presenting a topology-based approach that enables model predictive control (MPC) to simultaneously plan full-body motions, torque commands, footstep placements, and contact surfaces in real time. To determine if a robot's foot is inside a contact surface, we borrow the winding number concept from topology. We then use this winding number and potential field to create a contact-surface penalty function. By using this penalty function, MPC can select a contact surface from all candidate surfaces in the vicinity and determine footstep placements within it. We demonstrate the benefits of our approach by showing the impact of considering full-body dynamics, which includes joint torque limits and limb dynamics, on the selection of footstep placements and contact surfaces. Furthermore, we validate the feasibility of deploying our topology-based approach in an MPC scheme and explore its potential capabilities through a series of experimental and simulation trials.
Comments: 7 pages, 6 figures
Subjects: Robotics (cs.RO)
Cite as: arXiv:2303.13726 [cs.RO]
  (or arXiv:2303.13726v2 [cs.RO] for this version)
  https://doi.org/10.48550/arXiv.2303.13726
arXiv-issued DOI via DataCite
Journal reference: IEEE International Conference on Robotics and Automation (ICRA), 2023

Submission history

From: Carlos Mastalli [view email]
[v1] Fri, 24 Mar 2023 00:38:45 UTC (3,264 KB)
[v2] Sat, 29 Jul 2023 09:34:03 UTC (3,264 KB)
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