4 papers
GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning
GigaBrain Team, Boyuan Wang, Bohan Li +23
Vision-language-action (VLA) models that directly predict multi-step action chunks from current observations face inherent limitations due to constrained scene understanding and we…
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 Low-Dimensional Strain Models of Soft Robots by Looking at the Evolution of Their Shape with Application to Model-Based Control
Ricardo Valadas, Maximilian Stölzle, Jingyue Liu +1
Obtaining dynamic models of continuum soft robots is central to the analysis and control of soft robots, and researchers have devoted much attention to the challenge of proposing b…
EITNet: An IoT-Enhanced Framework for Real-Time Basketball Action Recognition
Jingyu Liu, Xinyu Liu, Mingzhe Qu +1
Integrating IoT technology into basketball action recognition enhances sports analytics, providing crucial insights into player performance and game strategy. However, existing met…