1 citations · 3 across the 5 of their papers we have counts for
6 papers
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…
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.…
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning
Charles Xu, Qiyang Li, Jianlan Luo +1
Recent advances in robotic foundation models have enabled the development of generalist policies that can adapt to diverse tasks. While these models show impressive flexibility, th…
Multi-View Pose-Agnostic Change Localization with Zero Labels
Chamuditha Jayanga Galappaththige, Jason Lai, Lloyd Windrim +3
Autonomous agents often require accurate methods for detecting and localizing changes in their environment, particularly when observations are captured from unconstrained and incon…
Reducing Label Dependency for Underwater Scene Understanding: A Survey of Datasets, Techniques and Applications
Scarlett Raine, Frederic Maire, Niko Suenderhauf +1
Underwater surveys provide long-term data for informing management strategies, monitoring coral reef health, and estimating blue carbon stocks. Advances in broad-scale survey metho…
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…