1 citations · 3 across the 4 of their papers we have counts for
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cs.RO2023
MOMA-Force: Visual-Force Imitation for Real-World Mobile Manipulation
Taozheng Yang, Ya Jing, Hongtao Wu +5
In this paper, we present a novel method for mobile manipulators to perform multiple contact-rich manipulation tasks. While learning-based methods have the potential to generate ac…
cs.RO2023★ 1 cited
Exploring Visual Pre-training for Robot Manipulation: Datasets, Models and Methods
Ya Jing, Xuelin Zhu, Xingbin Liu +4
Visual pre-training with large-scale real-world data has made great progress in recent years, showing great potential in robot learning with pixel observations. However, the recipe…
cs.RO2023★ 1 cited
Learning to Explore Informative Trajectories and Samples for Embodied Perception
Ya Jing, Tao Kong
We are witnessing significant progress on perception models, specifically those trained on large-scale internet images. However, efficiently generalizing these perception models to…