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20162024
most cited3D Simulation for Robot Arm Control with Deep Q-Learning

67 citations · 78 across the 6 of their papers we have counts for

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6 papers · 1 filter

cs.RO2024

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…

cs.RO2024

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…

cs.RO20241 cited

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…

cs.RO2023

Language-Conditioned Path Planning

Amber Xie, Youngwoon Lee, Pieter Abbeel +1

Contact is at the core of robotic manipulation. At times, it is desired (e.g. manipulation and grasping), and at times, it is harmful (e.g. when avoiding obstacles). However, tradi…

cs.RO20236 cited

Multi-View Masked World Models for Visual Robotic Manipulation

Younggyo Seo, Junsu Kim, Stephen James +3

Visual robotic manipulation research and applications often use multiple cameras, or views, to better perceive the world. How else can we utilize the richness of multi-view data? I…

cs.RO201667 cited

3D Simulation for Robot Arm Control with Deep Q-Learning

Stephen James, Edward Johns

Recent trends in robot arm control have seen a shift towards end-to-end solutions, using deep reinforcement learning to learn a controller directly from raw sensor data, rather tha…