ACFR Papers at IROS 2021
Check out our latest work! ACFR researchers will be presenting the following papers at the upcoming IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2021), to be held Sep 7 – Oct 1:
![](https://i0.wp.com/robotics.sydney.edu.au/wp-content/uploads/2021/08/a.png?resize=1024%2C916&ssl=1)
Fast-Learning Grasping and Pre-Grasping via Clutter Quantization and Q-map Masking
Dafa Ren, Xiaoqiang Ren, Xiaofan Wang, S. Tejaswi Digumarti, and Guodong Shi
Preprint: https://arxiv.org/abs/2107.02452
![](https://i0.wp.com/robotics.sydney.edu.au/wp-content/uploads/2021/08/65A38EFE966248F3AECF7E122989E59B.png?resize=481%2C371&ssl=1)
Anisotropic Disturbance Rejection for Kinematically Redundant Systems With Applications on an UVMS
Wilhelm Johan Marais, Stefan Williams, and Oscar Pizarro
![](https://i0.wp.com/robotics.sydney.edu.au/wp-content/uploads/2021/08/LFRefract.jpg?resize=1024%2C992&ssl=1)
Refractive light-field features for curved transparent objects in structure from motion
Dorian Tsai, Peter Corke, Thierry Peynot, Donald G. Dansereau
Preprint, dataset and code: https://roboticimaging.org/Projects/LFRefract/
![](https://i0.wp.com/robotics.sydney.edu.au/wp-content/uploads/2021/08/LearnLFOdoMain.jpg?resize=1024%2C896&ssl=1)
Learning to See with Sparse Light Field Video Cameras
S. Tejaswi Digumarti, Joseph Daniel, Ahalya Ravendran, Ryan Griffiths, and Donald G. Dansereau
Preprint, dataset and code: https://roboticimaging.org/Projects/LearnLFOdo/