67 citations · 100 across the 4 of their papers we have counts for
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cs.RO2023
Crossing the Reality Gap in Tactile-Based Learning
Ya-Yen Tsai, Bidan Huang, Yu Zheng +3
Tactile sensors are believed to be essential in robotic manipulation, and prior works often rely on experts to reason the sensor feedback and design a controller. With the recent a…
cs.RO2016★ 67 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…
cs.RO2016★ 33 cited
Deep Learning a Grasp Function for Grasping under Gripper Pose Uncertainty
Edward Johns, Stefan Leutenegger, Andrew J. Davison
This paper presents a new method for parallel-jaw grasping of isolated objects from depth images, under large gripper pose uncertainty. Whilst most approaches aim to predict the si…