4 citations · 4 across the 5 of their papers we have counts for
5 papers
Contact SLAM: An Active Tactile Exploration Policy Based on Physical Reasoning Utilized in Robotic Fine Blind Manipulation Tasks
Gaozhao Wang, Xing Liu, Zhenduo Ye +2
Contact-rich manipulation is difficult for robots to execute and requires accurate perception of the environment. In some scenarios, vision is occluded. The robot can then no longe…
Curiosity-Diffuser: Curiosity Guide Diffusion Models for Reliability
Zihao Liu, Xing Liu, Yuhang Dong +3
One of the bottlenecks in robotic intelligence is the instability of neural network models. This leads to risks when applying intelligence in the physical world. Specifically, imit…
Semantic-Geometric-Physical-Driven Robot Manipulation Skill Transfer via Skill Library and Tactile Representation
Mingchao Qi, Yuanjin Li, Xing Liu +2
Developing general robotic systems capable of manipulating in unstructured environments is a significant challenge, particularly as the tasks involved are typically long-horizon an…
Aligning Human Intent from Imperfect Demonstrations with Confidence-based Inverse soft-Q Learning
Xizhou Bu, Wenjuan Li, Zhengxiong Liu +2
Imitation learning attracts much attention for its ability to allow robots to quickly learn human manipulation skills through demonstrations. However, in the real world, human demo…
Tactile Active Inference Reinforcement Learning for Efficient Robotic Manipulation Skill Acquisition
Zihao Liu, Xing Liu, Yizhai Zhang +2
Robotic manipulation holds the potential to replace humans in the execution of tedious or dangerous tasks. However, control-based approaches are not suitable due to the difficulty…