Proprioceptive Actuator Design in the MIT Cheetah: Impact Mitigation and High-Bandwidth Physical Interaction for Dynamic Legged Robots

By Patrick M. Wensing, Albert Wang, Sangok Seok, D. Otten, J. Lang, Sangbae Kim. IEEE Transactions on robotics, 2017

424 citations recorded by the source corpus.

Designing an actuator system for highly dynamic legged robots has been one of the grand challenges in robotics research. Conventional actuators for manufacturing applications have difficulty satisfying design requirements for high-speed locomotion, such as the need for high torque density and the ability to manage dynamic physical interactions. To address this challenge, this paper suggests a proprioceptive actuation paradigm that enables highly dynamic performance in legged machines. Proprioceptive actuation uses collocated force control at the joints to effectively control contact interactions at the feet under dynamic conditions. Modal analysis of a reduced leg model and dimensional analysis of DC motors address the main principles for implementation of this paradigm. In the realm of legged machines, this paradigm provides a unique combination of high torque density, high-bandwidth force control, and the ability to mitigate impacts through backdrivability. We introduce a new metric named the “impact mitigation factor” (IMF) to quantify backdrivability at impact, which enables design comparison across a wide class of robots. The MIT Cheetah leg is presented, and is shown to have an IMF that is comparable to other quadrupeds with series springs to handle impact. The design enables the Cheetah to control contact forces during dynamic bounding, with contact times down to 85 ms and peak forces over 450 N. The unique capabilities of the MIT Cheetah, achieving impact-robust force-controlled operation in high-speed three-dimensional running and jumping, suggest wider implementation of this holistic actuation approach.

Subfields: Biomedical Engineering

View Paper: https://www.semanticscholar.org/paper/793f0a0c2ee71d20f719557ab5d90636963f62a1

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In Biomedical Engineering

  1. Benjamin Katz
  2. Jared Di Carlo
  3. Sangbae Kim
  4. Gerardo Bledt
  5. Patrick M. Wensing
  6. Avik De
  7. Gabriel B. Margolis
  8. Jie Tan

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