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Cited by 548

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Virtual Model Control: An Intuitive Approach for Bipedal Locomotion

Pratt, Jerry, Chew, Chee-Meng, Torres, Ann, Dilworth, Peter, Pratt, Gill·2001·The International Journal of Robotics Research

Abstract

Virtual model control is a motion control framework that uses virtual components to create virtual forces generated when the virtual components interact with a robot system. An algorithm derived based on the virtual model control framework is applied to a physical planar bipedal robot. It uses a simple set of virtual components that allows the robot to walk successfully over level terrain. This paper also describes how the algorithm can be augmented for rough terrain walking based on geometric consideration. The resulting algorithm is very simple and does not require the biped to have an extensive sensory system. The robot does not know the slope gradients and transition locations in advance. The ground is detected using foot contact switches. Using the algorithm, we have successfully compelled a simulated seven-link planar biped to walk blindly up and down slopes and over rolling terrain.

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Crossref · 10.1177/02783640122067309

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Metadata

Authors
Pratt, J., Chew, C.-M., Torres, A., Dilworth, P., & Pratt, G.
Venue
The International Journal of Robotics Research
Published
2001-02
Volume
20
Issue
2
Pages
129-143
ISSN
  • 0278-3649 (ISSN-L)
  • 1741-3176
OpenAlex
W2086587468
Cited by
548
References
2
FWCI
3.08
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Virtual Model Control: An Intuitive Approach for Bipedal Locomotion. https://app.cochat.ai/papers/10.1177/02783640122067309
The paper
Pratt, J., Chew, C.-M., Torres, A., Dilworth, P., & Pratt, G. (2001). Virtual Model Control: An Intuitive Approach for Bipedal Locomotion. The International Journal of Robotics Research. https://doi.org/10.1177/02783640122067309

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.