Model predictive control (MPC) of legged and humanoid robotic systems has been an active
research topic in the past decade. While MPC for robotic systems has a long history, its …

In this paper, a hierarchical and robust framework for learning bipedal locomotion is
presented and successfully implemented on the 3D biped robot Digit built by Agility …

This paper presents a Non-Linear Model Predictive Controller for humanoid robot
locomotion with online step adjustment capabilities. The proposed controller considers the …

In this paper, we propose a biped walking controller that optimized three push recovery
strategies: the ankle, hip, and stepping strategies. We suggested formulations that related …

In this letter, an integrated control strategy is developed for both locomotion trajectory
planning and postural stability, enabling shared autonomy between the human and lower …

Robust locomotion is a challenging task for humanoid robots, especially when considering
dynamic disturbances. This article proposes a disturbance observer-based cascaded model …

Animals locomote robustly and agile, albeit significant sensorimotor delays of their nervous
system and the harsh loading conditions resulting from repeated, high-frequent impacts. The …

We present a real time algorithm for humanoid 3D walking and/or running based on a Model
Predictive Control (MPC) approach. The objective is to generate a stable gait that replicates …

Wearable walking exoskeletons show great potentials in helping patients with neuro
musculoskeletal stroke. Key to the successful applications is the design of effective walking …

We present a computationally efficient method for online planning of bipedal walking
trajectories with push recovery. In particular, the proposed methodology fits control …