In this letter, we propose a locomotion training framework where a control policy and a state
estimator are trained concurrently. The framework consists of a policy network which outputs …

A climbing robot that can rapidly move on diverse surfaces such as floors, walls, and ceilings
will have an enlarged operational workspace compared with other terrestrial robots …

As the study of humanoid robots becomes a world-wide interdisciplinary research field, the
demand for a cost-effective bipedal robot system capable of dynamic behaviors is growing …

Robotic systems usually evolve on manifolds, which are often overparameterized or
minimally parameterized (but with singularities) in model predictive control (MPC). How to …

This paper presents a contact-implicit model predictive control (MPC) framework for the real-
time discovery of multi-contact motions, without predefined contact mode sequences or …

This paper reports on a new error-state Model Predictive Control (MPC) approach to
connected matrix Lie groups for robot control. The linearized tracking error dynamics and the …

Control of legged robots is a challenging problem that has been investigated by different
approaches, such as model-based control and learning algorithms. This work proposes a …

This paper introduces a design method for an efficient and agile quadruped robot. A mixed-
integer optimization formulation including the number of gear teeth is derived to obtain the …

In this paper, we present a framework rooted in control and planning that enables
quadrupedal robots to traverse challenging terrains with discrete footholds using visual …

In this work, a non-gaited framework for legged system locomotion is presented. The
approach decouples the gait sequence optimization by considering the problem as a …