254 citations · 884 across the 46 of their papers we have counts for
5 papers · 1 filter
Learning Multi-Arm Manipulation Through Collaborative Teleoperation
Albert Tung, Josiah Wong, Ajay Mandlekar +4
Imitation Learning (IL) is a powerful paradigm to teach robots to perform manipulation tasks by allowing them to learn from human demonstrations collected via teleoperation, but ha…
Human-in-the-Loop Imitation Learning using Remote Teleoperation
Ajay Mandlekar, Danfei Xu, Roberto Martín-Martín +3
Imitation Learning is a promising paradigm for learning complex robot manipulation skills by reproducing behavior from human demonstrations. However, manipulation tasks often conta…
Deep Affordance Foresight: Planning Through What Can Be Done in the Future
Danfei Xu, Ajay Mandlekar, Roberto Martín-Martín +3
Planning in realistic environments requires searching in large planning spaces. Affordances are a powerful concept to simplify this search, because they model what actions can be s…
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
Yuke Zhu, Josiah Wong, Ajay Mandlekar +6
robosuite is a simulation framework for robot learning powered by the MuJoCo physics engine. It offers a modular design for creating robotic tasks as well as a suite of benchmark e…
Learning to Generalize Across Long-Horizon Tasks from Human Demonstrations
Ajay Mandlekar, Danfei Xu, Roberto Martín-Martín +2
Imitation learning is an effective and safe technique to train robot policies in the real world because it does not depend on an expensive random exploration process. However, due…