Virtual Model Control: An Intuitive Approach for Bipedal Locomotion

By Jerry E. Pratt, Chee-Meng Chew, A. Torres, Peter Dilworth, G. Pratt. Int. J. Robotics Res., 2001

634 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/6ac9b45edb830c31772f1033a72aaaf39eb2c80c

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In Biomedical Engineering

In Control and Systems Engineering

Citations in the corpus

Deep reinforcement learning for tensegrity robot locomotion (2016, background): “Previous work in robotic locomotion has produced successful bipedal locomotion using passive-dynamic walkers [24] and virtual model control [25], as well as springmass running based on biological models [26].”
Capturability-based analysis and control of legged locomotion, Part 2: Application to M2V2, a lower-body humanoid (2012, methodology): “Furthermore, the current part extends some of the control strategies from previous work (Pratt et al. 2001) to 3D.”
A Compliant Hybrid Zero Dynamics Controller for Stable, Efficient and Fast Bipedal Walking on MABEL (2011, methodology): “MIT’s Spring Flamingo achieved stable, efficient, and fast walking by employing Series Elastic Actuators (SEAs) and a virtual model controller (Pratt and Pratt 1998; Pratt 2000; Pratt et al. 2001).”
A Series Elastic- and Bowden-Cable-Based Actuation System for Use as Torque Actuator in Exoskeleton-Type Robots (2006, methodology): “…before, by Torres-Jara and Banks (2004), but that design was meant for use in the motor axis), integrated the actuator with the robot joint and added a Bowden cable transmission (common cable drives have been used with SEA before, for example in the " Spring Turkey " (Pratt et al. 2001)).”
Feedback Control of Dynamic Bipedal Robot Locomotion (2007, methodology): “[181] used what they termed “virtual model control.”
An Introduction to Trajectory Optimization: How to Do Your Own Direct Collocation (2017, methodology): “This model is commonly used when studying bipedal walking robots [25,43,48,54,66,67].”
Whole-Body Nonlinear Model Predictive Control Through Contacts for Quadrupeds (2017, methodology): “Lastly, we also add a virtual model controller [38] using inverse dynamics (without gravity compensation) which only contributes a few percent of the overall control signal.”
Models, feedback control, and open problems of 3D bipedal robotic walking (2014, methodology): “Inspired by Raibert's hoppers ([157], [160], [158]), and also by spring amingo and spring turkey ([73, 152, 150, 154]), Hurst designed the planar bipedal robot MABEL and the 3D bipedal robot ATRIAS to include large springs, as shown in Fig.”