7 citations · 32 across the 33 of their papers we have counts for
6 papers · 1 filter
Effective Tuning Strategies for Generalist Robot Manipulation Policies
Wenbo Zhang, Yang Li, Yanyuan Qiao +5
Generalist robot manipulation policies (GMPs) have the potential to generalize across a wide range of tasks, devices, and environments. However, existing policies continue to strug…
BiGym: A Demo-Driven Mobile Bi-Manual Manipulation Benchmark
Nikita Chernyadev, Nicholas Backshall, Xiao Ma +3
We introduce BiGym, a new benchmark and learning environment for mobile bi-manual demo-driven robotic manipulation. BiGym features 40 diverse tasks set in home environments, rangin…
Mixture of Experts based Multi-task Supervise Learning from Crowds
Tao Han, Huaixuan Shi, Xinyi Ding +3
Existing truth inference methods in crowdsourcing aim to map redundant labels and items to the ground truth. They treat the ground truth as hidden variables and use statistical or…
Green Screen Augmentation Enables Scene Generalisation in Robotic Manipulation
Eugene Teoh, Sumit Patidar, Xiao Ma +1
Generalising vision-based manipulation policies to novel environments remains a challenging area with limited exploration. Current practices involve collecting data in one location…
Redundancy-aware Action Spaces for Robot Learning
Pietro Mazzaglia, Nicholas Backshall, Xiao Ma +1
Joint space and task space control are the two dominant action modes for controlling robot arms within the robot learning literature. Actions in joint space provide precise control…
Hierarchical Diffusion Policy for Kinematics-Aware Multi-Task Robotic Manipulation
Xiao Ma, Sumit Patidar, Iain Haughton +1
This paper introduces Hierarchical Diffusion Policy (HDP), a hierarchical agent for multi-task robotic manipulation. HDP factorises a manipulation policy into a hierarchical struct…