115 citations · 128 across the 16 of their papers we have counts for
3 papers · 1 filter
Tactile Gym 2.0: Sim-to-real Deep Reinforcement Learning for Comparing Low-cost High-Resolution Robot Touch
Yijiong Lin, John Lloyd, Alex Church +1
High-resolution optical tactile sensors are increasingly used in robotic learning environments due to their ability to capture large amounts of data directly relating to agent-envi…
DigiTac: A DIGIT-TacTip Hybrid Tactile Sensor for Comparing Low-Cost High-Resolution Robot Touch
Nathan F. Lepora, Yijiong Lin, Ben Money-Coomes +1
Deep learning combined with high-resolution tactile sensing could lead to highly capable dexterous robots. However, progress is slow because of the specialist equipment and experti…
One-Shot Domain-Adaptive Imitation Learning via Progressive Learning
Dandan Zhang, Wen Fan, John Lloyd +2
Traditional deep learning-based visual imitation learning techniques require a large amount of demonstration data for model training, and the pre-trained models are difficult to ad…