3 papers
cs.RO2026
ELMP: Efficient Learning for Motion Planning via Analytical Policy Gradients
Yixiao Li, Tifanny Portela, Jordis Herrmann +2
Neural Motion Planners (NMPs) enable fast reactive motion generation, but adapting them to new environments typically requires recollecting large expert datasets, which is computat…
cs.RO2026
TactSpace: Learning a Physics-enriched Shared Latent Space for Tactile Sim-to-Real Transfer
Arunim Joarder, Arjun Bhardwaj, René Zurbrügg +6
Tactile sensing provides direct measurements of contact interactions that are essential for robotic manipulation. However, current simulators lack the fidelity to faithfully model…
cs.RO2026
Dense Force Estimation with an Event-based Optical Tactile Sensor
Agis Politis, René Zurbrügg, Valentina Cavinato
Humans rely on spatially dense, geometry and force-aware tactile feedback at high temporal resolution for dexterous manipulation. While vision-based tactile sensors enable dense fo…