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A Reactive Walking Pattern Generator Based on Nonlinear Model Predictive Control

Abstract : The contribution of this work is to show that real-time nonlinear model predictive control (NMPC) can be implemented on position controlled humanoid robots. Following the idea of " walking without thinking " , we propose a walking pattern generator that takes into account simultaneously the position and orientation of the feet. A requirement for an application in real-world scenarios is the avoidance of obstacles. Therefore the paper shows an extension of the pattern generator that directly considers the avoidance of convex obstacles. The algorithm uses the whole-body dynamics to correct the center of mass trajectory of the underlying simplified model. The pattern generator runs in real-time on the embedded hardware of the humanoid robot HRP-2 and experiments demonstrate the increase in performance with the correction.
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Submitted on : Monday, January 25, 2016 - 11:56:25 AM
Last modification on : Monday, July 4, 2022 - 8:59:56 AM
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Maximilien Naveau, Manuel Kudruss, Olivier Stasse, Christian Kirches, Katja Mombaur, et al.. A Reactive Walking Pattern Generator Based on Nonlinear Model Predictive Control. IEEE Robotics and Automation Letters, IEEE 2017, 2 (1), pp.10-17. ⟨10.1109/LRA.2016.2518739⟩. ⟨hal-01261415⟩



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