TY - GEN
T1 - Moving sidewinding forward
T2 - 17th Robotics: Science and Systems, RSS 2021
AU - Chong, Baxi
AU - Wang, Tianyu
AU - Lin, Bo
AU - Li, Shengkai
AU - Blekherman, Grigoriy
AU - Choset, Howie
AU - Goldman, Daniel I.
N1 - Publisher Copyright:
© 2021, MIT Press Journals, All rights reserved.
PY - 2021
Y1 - 2021
N2 - Contact planning is crucial to the locomotion performance of limbless robots. Typically, the pattern by which contact is made and broken between the mechanism and its environment determines the motion of the robot. The design of these patterns, often called contact patterns, is a difficult problem. In previous work, the prescription of contact patterns was derived from observations of biological systems or determined empirically from black-box optimization algorithms. However, such contact pattern prescription is only applicable to specific mechanisms, and is challenging to generalize. For example, the stable and effective contact pattern prescribed for a 12-link limbless robot can be neither stable nor effective for a 6-link limbless robot. In this paper, using a geometric motion planning scheme, we develop a framework to design, optimize, and analyze contact patterns to generate effective motion in the desired directions. Inspired by prior work in geometric mechanics, we separate the configuration space into a shape space (the internal joint angles), a contact state space, and a position space; then we optimize the function that couples the contact state space and the shape space. Our framework provides physical insights into the contact pattern design and reveals principles of empirically derived contact pattern prescriptions. Applying this framework, we can not only control the direction of motion of a 12-link limbless robot by modulating the contact patterns, but also design effective sidewinding gaits for robots with fewer motors (e.g., a 6-link robot). We test our designed gaits by robophysical experiments and obtain excellent agreement. We expect our scheme can be broadly applicable to robots which make/break contact.
AB - Contact planning is crucial to the locomotion performance of limbless robots. Typically, the pattern by which contact is made and broken between the mechanism and its environment determines the motion of the robot. The design of these patterns, often called contact patterns, is a difficult problem. In previous work, the prescription of contact patterns was derived from observations of biological systems or determined empirically from black-box optimization algorithms. However, such contact pattern prescription is only applicable to specific mechanisms, and is challenging to generalize. For example, the stable and effective contact pattern prescribed for a 12-link limbless robot can be neither stable nor effective for a 6-link limbless robot. In this paper, using a geometric motion planning scheme, we develop a framework to design, optimize, and analyze contact patterns to generate effective motion in the desired directions. Inspired by prior work in geometric mechanics, we separate the configuration space into a shape space (the internal joint angles), a contact state space, and a position space; then we optimize the function that couples the contact state space and the shape space. Our framework provides physical insights into the contact pattern design and reveals principles of empirically derived contact pattern prescriptions. Applying this framework, we can not only control the direction of motion of a 12-link limbless robot by modulating the contact patterns, but also design effective sidewinding gaits for robots with fewer motors (e.g., a 6-link robot). We test our designed gaits by robophysical experiments and obtain excellent agreement. We expect our scheme can be broadly applicable to robots which make/break contact.
UR - https://www.scopus.com/pages/publications/85127969809
UR - https://www.scopus.com/pages/publications/85127969809#tab=citedBy
U2 - 10.15607/RSS.2021.XVII.031
DO - 10.15607/RSS.2021.XVII.031
M3 - Conference contribution
AN - SCOPUS:85127969809
SN - 9780992374778
T3 - Robotics: Science and Systems
BT - Robotics
A2 - Shell, Dylan A.
A2 - Toussaint, Marc
A2 - Hsieh, M. Ani
PB - Massachusetts Institute of Technology
Y2 - 12 July 2021 through 16 July 2021
ER -