62 citations · 109 across the 3 of their papers we have counts for
5 papers
BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
Sanjana Srivastava, Chengshu Li, Michael Lingelbach +11
We introduce BEHAVIOR, a benchmark for embodied AI with 100 activities in simulation, spanning a range of everyday household chores such as cleaning, maintenance, and food preparat…
iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks
Chengshu Li, Fei Xia, Roberto Martín-Martín +13
Recent research in embodied AI has been boosted by the use of simulation environments to develop and train robot learning approaches. However, the use of simulation has skewed the…
iGibson 1.0: a Simulation Environment for Interactive Tasks in Large Realistic Scenes
Bokui Shen, Fei Xia, Chengshu Li +12
We present iGibson 1.0, a novel simulation environment to develop robotic solutions for interactive tasks in large-scale realistic scenes. Our environment contains 15 fully interac…
ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation
Fei Xia, Chengshu Li, Roberto Martín-Martín +3
Many Reinforcement Learning (RL) approaches use joint control signals (positions, velocities, torques) as action space for continuous control tasks. We propose to lift the action s…
HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators
Chengshu Li, Fei Xia, Roberto Martin-Martin +1
Most common navigation tasks in human environments require auxiliary arm interactions, e.g. opening doors, pressing buttons and pushing obstacles away. This type of navigation task…