14 citations · 21 across the 10 of their papers we have counts for
10 papers
UnSAMFlow: Unsupervised Optical Flow Guided by Segment Anything Model
Shuai Yuan, Lei Luo, Zhuo Hui +4
Traditional unsupervised optical flow methods are vulnerable to occlusions and motion boundaries due to lack of object-level information. Therefore, we propose UnSAMFlow, an unsupe…
Learning Quadruped Locomotion using Bio-Inspired Neural Networks with Intrinsic Rhythmicity
Chuanyu Yang, Can Pu, Tianqi Wei +2
Biological studies reveal that neural circuits located at the spinal cord called central pattern generator (CPG) oscillates and generates rhythmic signals, which are the underlying…
A Multi-modal Garden Dataset and Hybrid 3D Dense Reconstruction Framework Based on Panoramic Stereo Images for a Trimming Robot
Can Pu, Chuanyu Yang, Jinnian Pu +2
Recovering an outdoor environment's surface mesh is vital for an agricultural robot during task planning and remote visualization. Our proposed solution is based on a newly-designe…
A General Mobile Manipulator Automation Framework for Flexible Manufacturing in Hostile Industrial Environments
Can Pu, Chuanyu Yang, Jinnian Pu +1
To enable a mobile manipulator to perform human tasks from a single teaching demonstration is vital to flexible manufacturing. We call our proposed method MMPA (Mobile Manipulator…
Incremental Non-Gaussian Inference for SLAM Using Normalizing Flows
Qiangqiang Huang, Can Pu, Kasra Khosoussi +4
This paper presents normalizing flows for incremental smoothing and mapping (NF-iSAM), a novel algorithm for inferring the full posterior distribution in SLAM problems with nonline…
NF-iSAM: Incremental Smoothing and Mapping via Normalizing Flows
Qiangqiang Huang, Can Pu, Dehann Fourie +3
This paper presents a novel non-Gaussian inference algorithm, Normalizing Flow iSAM (NF-iSAM), for solving SLAM problems with non-Gaussian factors and/or non-linear measurement mod…