226 citations · 1k across the 102 of their papers we have counts for
14 papers · 1 filter
OpenD: A Benchmark for Language-Driven Door and Drawer Opening
Yizhou Zhao, Qiaozi Gao, Liang Qiu +2
We introduce OPEND, a benchmark for learning how to use a hand to open cabinet doors or drawers in a photo-realistic and physics-reliable simulation environment driven by language…
CLIP-Nav: Using CLIP for Zero-Shot Vision-and-Language Navigation
Vishnu Sashank Dorbala, Gunnar Sigurdsson, Robinson Piramuthu +2
Household environments are visually diverse. Embodied agents performing Vision-and-Language Navigation (VLN) in the wild must be able to handle this diversity, while also following…
Efficiently Learning Small Policies for Locomotion and Manipulation
Shashank Hegde, Gaurav S. Sukhatme
Neural control of memory-constrained, agile robots requires small, yet highly performant models. We leverage graph hyper networks to learn graph hyper policies trained with off-pol…
CH-MARL: A Multimodal Benchmark for Cooperative, Heterogeneous Multi-Agent Reinforcement Learning
Vasu Sharma, Prasoon Goyal, Kaixiang Lin +3
We propose a multimodal (vision-and-language) benchmark for cooperative and heterogeneous multi-agent learning. We introduce a benchmark multimodal dataset with tasks involving col…
Decentralized Risk-Aware Tracking of Multiple Targets
Jiazhen Liu, Lifeng Zhou, Ragesh Ramachandran +2
We consider the setting where a team of robots is tasked with tracking multiple targets with the following property: approaching the targets enables more accurate target position e…
Learning Deformable Object Manipulation from Expert Demonstrations
Gautam Salhotra, I-Chun Arthur Liu, Marcus Dominguez-Kuhne +1
We present a novel Learning from Demonstration (LfD) method, Deformable Manipulation from Demonstrations (DMfD), to solve deformable manipulation tasks using states or images as in…