Shengkai Liu — accepted AI-conference papers

2024

A2G: Leveraging Intuitive Physics for Force-Efficient Robotic Grasping

Yaofeng Cheng, Shengkai Liu, Fusheng Zha, Wei Guo, Haoyu Du, Pengfei Wang +1

RA-L 2024

In object manipulation, movements are inherently restricted by object geometry and dynamics. Humans use an intuitive understanding of physics while grasping objects, resulting in an efficient application of manipulation force. This involves a ‘common sense’ awareness of how objects behave in the phy

Cited by 1 Source ↗Scholar ↗

2021

Co-Optimization of Morphology and Actuation Parameters of Multi-Sectional FREEs for Trajectory Matching

Wenjun Xu, Shengkai Liu, Wenchao Kong, Chao Wang, Hao Deng, Tao Mei

RA-L 2021

Fiber Reinforced Elastomeric Enclosures (FREEs) have gained significant popularity as a form of soft artificial muscle for the diversified deformation behaviors upon pressurization. In particular, modular FREEs connected in series, demonstrate enhanced flexibility and reconfigurability, thus are ada

Cited by 1 Source ↗Scholar ↗