2 citations · 2 across the 1 of their papers we have counts for
7 papers
Advanced Skills through Multiple Adversarial Motion Priors in Reinforcement Learning
Eric Vollenweider, Marko Bjelonic, Victor Klemm +3
In recent years, reinforcement learning (RL) has shown outstanding performance for locomotion control of highly articulated robotic systems. Such approaches typically involve tedio…
CERBERUS: Autonomous Legged and Aerial Robotic Exploration in the Tunnel and Urban Circuits of the DARPA Subterranean Challenge
Marco Tranzatto, Frank Mascarich, Lukas Bernreiter +38
Autonomous exploration of subterranean environments constitutes a major frontier for robotic systems as underground settings present key challenges that can render robot autonomy h…
Collision-Free MPC for Legged Robots in Static and Dynamic Scenes
Magnus Gaertner, Marko Bjelonic, Farbod Farshidian +1
We present a model predictive controller (MPC) that automatically discovers collision-free locomotion while simultaneously taking into account the system dynamics, friction constra…
Whole-Body MPC and Online Gait Sequence Generation for Wheeled-Legged Robots
Marko Bjelonic, Ruben Grandia, Oliver Harley +3
Our paper proposes a model predictive controller as a single-task formulation that simultaneously optimizes wheel and torso motions. This online joint velocity and ground reaction…
Rolling in the Deep -- Hybrid Locomotion for Wheeled-Legged Robots using Online Trajectory Optimization
Marko Bjelonic, Prajish K. Sankar, C. Dario Bellicoso +2
Wheeled-legged robots have the potential for highly agile and versatile locomotion. The combination of legs and wheels might be a solution for any real-world application requiring…
Walking Posture Adaptation for Legged Robot Navigation in Confined Spaces
Russell Buchanan, Tirthankar Bandyopadhyay, Marko Bjelonic +3
Legged robots have the ability to adapt their walking posture to navigate confined spaces due to their high degrees of freedom. However, this has not been exploited in most common…