Learning-based legged locomotion: State of the art and future perspectives

S Ha, J Lee, M van de Panne, Z **
Z He, J Wu, J Zhang, S Zhang, Y Shi… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
Performing acrobatic maneuvers like dynamic jum** in bipedal robots presents significant
challenges in terms of actuation, motion planning, and control. Traditional approaches to …

Consensus complementarity control for multi-contact mpc

A Aydinoglu, A Wei, WC Huang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
We propose a hybrid model predictive control algorithm, consensus complementarity
control, for systems that make and break contact with their environment. Many state-of-the …

Mpcgpu: Real-time nonlinear model predictive control through preconditioned conjugate gradient on the gpu

E Adabag, M Atal, W Gerard… - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
Nonlinear Model Predictive Control (NMPC) is a state-of-the-art approach for locomotion
and manipulation which leverages trajectory optimization at each control step. While the …

Towards tight convex relaxations for contact-rich manipulation

BP Graesdal, SYC Chia, T Marcucci, S Morozov… - arxiv preprint arxiv …, 2024 - arxiv.org
We present a novel method for global motion planning of robotic systems that interact with
the environment through contacts. Our method directly handles the hybrid nature of such …