6 papers
SG-CoT: An Ambiguity-Aware Robotic Planning Framework using Scene Graph Representations
Akshat Rana, Peeyush Agarwal, K. P. S. Rana +1
Ambiguity poses a major challenge to large language models (LLMs) used as robotic planners. In this letter, we present Scene Graph-Chain-of-Thought (SG-CoT), a two-stage framework…
Learning from 10 Demos: Generalisable and Sample-Efficient Policy Learning with Oriented Affordance Frames
Krishan Rana, Jad Abou-Chakra, Sourav Garg +3
Imitation learning has unlocked the potential for robots to exhibit highly dexterous behaviours. However, it still struggles with long-horizon, multi-object tasks due to poor sampl…
Real-is-Sim: Bridging the Sim-to-Real Gap with a Dynamic Digital Twin
Jad Abou-Chakra, Lingfeng Sun, Krishan Rana +5
We introduce real-is-sim, a new approach to integrating simulation into behavior cloning pipelines. In contrast to real-only methods, which lack the ability to safely test policies…
Open X-Embodiment: Robotic Learning Datasets and RT-X Models
Embodiment Collaboration, Abby O'Neill, Abdul Rehman +291
Large, high-capacity models trained on diverse datasets have shown remarkable successes on efficiently tackling downstream applications. In domains from NLP to Computer Vision, thi…
IMLE Policy: Fast and Sample Efficient Visuomotor Policy Learning via Implicit Maximum Likelihood Estimation
Krishan Rana, Robert Lee, David Pershouse +1
Recent advances in imitation learning, particularly using generative modelling techniques like diffusion, have enabled policies to capture complex multi-modal action distributions.…
Multi-Modal 3D Scene Graph Updater for Shared and Dynamic Environments
Emilio Olivastri, Jonathan Francis, Alberto Pretto +2
The advent of generalist Large Language Models (LLMs) and Large Vision Models (VLMs) have streamlined the construction of semantically enriched maps that can enable robots to groun…