14 citations · 50 across the 32 of their papers we have counts for
9 papers · 2 filters
Symbolic Learning of Interpretable Reduced-Order Models for Jumping Quadruped Robots
Gioele Buriani, Jingyue Liu, Maximilian Stölzle +2
Reduced-order models are central to motion planning and control of quadruped robots, yet existing templates are often hand-crafted for a specific locomotion modality. This motivate…
Learning to Move in Rhythm: Task-Conditioned Motion Policies with Orbital Stability Guarantees
Maximilian Stölzle, T. Konstantin Rusch, Zach J. Patterson +5
Learning from demonstration provides a sample-efficient approach to acquiring complex behaviors, enabling robots to move robustly, compliantly, and with fluidity. In this context,…
A Survey on Soft Robot Adaptability: Implementations, Applications, and Prospects
Zixi Chen, Di Wu, Qinghua Guan +8
Soft robots, compared to rigid robots, possess inherent advantages, including higher degrees of freedom, compliance, and enhanced safety, which have contributed to their increasing…
Contact-Aware Safety in Soft Robots Using High-Order Control Barrier and Lyapunov Functions
Kiwan Wong, Maximilian Stölzle, Wei Xiao +3
Robots operating alongside people, particularly in sensitive scenarios such as aiding the elderly with daily tasks or collaborating with workers in manufacturing, must guarantee sa…
Soft yet Effective Robots via Holistic Co-Design
Maximilian Stölzle, Niccolò Pagliarani, Francesco Stella +6
Soft robots promise inherent safety via their material compliance for seamless interactions with humans or delicate environments. Yet, their development is challenging because it r…
Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learning
Georgios Apostolides, Wei Pan, Jens Kober +2
Achieving controlled jumping behaviour for a quadruped robot is a challenging task, especially when introducing passive compliance in mechanical design. This study addresses this c…