Manipulation Task
Robotic manipulation research focuses on enabling robots to perform complex tasks involving object interaction, driven by the need for more adaptable and robust automation. Current efforts center on developing vision-language-action models, often leveraging large language models and deep reinforcement learning, to translate natural language instructions and visual input into precise robot actions, with a strong emphasis on improving robustness and generalization across diverse scenarios and objects. This field is crucial for advancing robotics in various sectors, from manufacturing and logistics to assistive technologies, by creating robots capable of understanding and responding to complex, real-world instructions.
Papers
Visual Robotic Manipulation with Depth-Aware Pretraining
Wanying Wang, Jinming Li, Yichen Zhu, Zhiyuan Xu, Zhengping Che, Yaxin Peng, Chaomin Shen, Dong Liu, Feifei Feng, Jian Tang
SWBT: Similarity Weighted Behavior Transformer with the Imperfect Demonstration for Robotic Manipulation
Kun Wu, Ning Liu, Zhen Zhao, Di Qiu, Jinming Li, Zhengping Che, Zhiyuan Xu, Qinru Qiu, Jian Tang
Generalizable Long-Horizon Manipulations with Large Language Models
Haoyu Zhou, Mingyu Ding, Weikun Peng, Masayoshi Tomizuka, Lin Shao, Chuang Gan
STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent
Yewon Lee, Philip Huang, Krishna Murthy Jatavallabhula, Andrew Z. Li, Fabian Damken, Eric Heiden, Kevin Smith, Derek Nowrouzezahrai, Fabio Ramos, Florian Shkurti
Coupled Active Perception and Manipulation Planning for a Mobile Manipulator in Precision Agriculture Applications
Shuangyu Xie, Chengsong Hu, Di Wang, Joe Johnson, Muthukumar Bagavathiannan, Dezhen Song
Perceiving Extrinsic Contacts from Touch Improves Learning Insertion Policies
Carolina Higuera, Joseph Ortiz, Haozhi Qi, Luis Pineda, Byron Boots, Mustafa Mukadam
D$^3$Fields: Dynamic 3D Descriptor Fields for Zero-Shot Generalizable Rearrangement
Yixuan Wang, Mingtong Zhang, Zhuoran Li, Tarik Kelestemur, Katherine Driggs-Campbell, Jiajun Wu, Li Fei-Fei, Yunzhu Li