9 papers
Trust Region Inverse Reinforcement Learning: Explicit Dual Ascent using Local Policy Updates
Anish Diwan, Davide Tateo, Christopher E. Mower +3
Inverse reinforcement learning (IRL) is typically formulated as maximizing entropy subject to matching the distribution of expert trajectories. Classical (dual-ascent) IRL guarante…
HapTile: A Haptic-Informed Vision-Tactile-Language-Action Dataset for Contact-Rich Imitation Learning
Amirhosein Alian, Yongqiang Zhao, Shiyi Gu +5
Despite the importance of tactile sensing for reliable manipulation, most existing Vision-Language-Action (VLA) datasets remain vision-only, and those that do incorporate tactile i…
EmbodimentSemantic: A Spatial Scene-Graph Dataset and Benchmark for Vision-Language Models on Embodied Manipulation Trajectories
Hassan Jaber, Refinath S N, Luca Cagliero +2
Spatial grounding remains a key limitation of vision-language-action (VLA) systems for robotic manipulation. While current models can recognize objects and follow language instruct…
A Pragmatist Robot: Learning to Plan Tasks by Experiencing the Real World
Kaixian Qu, Guowei Lan, René Zurbrügg +4
Large language models (LLMs) have emerged as the dominant paradigm for robotic task planning using natural language instructions. However, trained on general internet data, LLMs ar…
Data-driven Interpretable Hybrid Robot Dynamics
Christopher E. Mower, Rui Zong, Haitham Bou-Ammar
We study data-driven identification of interpretable hybrid robot dynamics, where an analytical rigid-body dynamics model is complemented by a learned residual torque term. Using s…
Localising under the drape: proprioception in the era of distributed surgical robotic system
Martin Huber, Nicola A. Cavalcanti, Ayoob Davoodi +15
Despite their mechanical sophistication, surgical robots remain blind to their surroundings. This lack of spatial awareness causes collisions, system recoveries, and workflow disru…