2 papers
cs.RO2026
Learning Contact Dynamics through Touching: Action-conditional Graph Neural Networks for Robotic Peg Insertion
Zongyao Yi, Joachim Hertzberg, Martin Atzmueller
We present a learnable physics-based predictive model that provides accurate motion and force-torque prediction of the robot end effector in contact-rich manipulation. The proposed…
cs.RO2026
Agentic AI for Robot Control: Flexible but still Fragile
Oscar Lima, Marc Vinci, Martin Günther +10
Recent work leverages the capabilities and commonsense priors of generative models for robot control. In this paper, we present an agentic control system in which a reasoning-capab…