2021

• Heng Yang and Luca Carlone, Certifiable Outlier-Robust Geometric Perception: Exact Semidefinite Relaxations and Scalable Global Optimization, 2021. (Code) — The paper to read about the line of research in designing certifiable and trustworthy algorithms for robot perception.

• Heng Yang, Ling Liang, Luca Carlone, and Kim-Chuan Toh, An Inexact Projected Gradient Method with Rounding and Lifting by Nonlinear Programming for Solving Rank-One Semidefinite Relaxation of Polynomial Optimization, 2021. (Code) — Introduce STRIDE, the first method that can solve large-scale rank-one semidefinite relaxations of polynomial optimization problems to high accuracy, even in the presence of millions of constraints.

• Jingnan Shi, Heng Yang, and Luca Carlone, Optimal Pose and Shape Estimation for Category-level 3D Object Perception, in Robotics: Science and Systems (RSS), 2021. Best Paper Award Finalist. (Spotlight Video) — Introduce PACE, a state-of-the-art optimal method for solving category-level object pose estimation such as estimating the pose of a car with unknown 3D CAD model.

• Heng Yang, Chris Doran, and Jean-Jacques Slotine, Dynamical Pose Estimation, 2021. (Video) — Introduce DAMP, the first general and practical algorithm for solving a class of pose estimation problems by simulating rigid body dynamics arising from virtual springs and damping.

• Heng Yang, Wei Dong, Luca Carlone, and Vladlen Koltun, Self-supervised Geometric Perception, In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2021. Oral presentation. (Code) —The first general and practical framework for learning feature descriptors without ground-truth supervision from geometric models. 

• Jingnan Shi, Heng Yang, and Luca Carlone, ROBIN: a Graph-Theoretic Approach to Reject Outliers in Robust Estimation using Invariants, In International Conference on Robotics and Automation (ICRA), 2021. —Boost the performance of robust solvers (RANSAC, GNC) like a charm!

2020

• Pasquale Antonante, Vasileios Tzoumas, Heng Yang, and Luca Carlone, Outlier-Robust Estimation: Hardness, Minimally-Tuned Algorithms, and Applications, IEEE Transactions on Robotics (T-RO), 2020. —The one paper to read to learn about robust estimation in robot perception.

• Heng Yang and Luca Carlone, One Ring to Rule Them All: Certifiably Robust Geometric Perception with Outliers, in Conference on Neural Information Processing Systems (NeurIPS), 2020. (Video)(Code) —Beyond TEASER: we extend the success of TEASER to solve a class of robust geometric perception problems with outliers. This is the first work in literature that can certifiably solve robust geometric perception problems.

• Heng Yang, A Dynamical Perspective on Point Cloud Registration, arXiv Preprint, 2020.

• Heng Yang, Jingnan Shi and Luca Carlone, TEASER: Fast and Certifiable Point Cloud Registration, in IEEE Transactions on Robotics (T-RO), 2020. (Code)(Video)(Tutorial) —TEASER is robust against over 99% outlier correspondences; TEASER is certifiably correct; TEASER runs in milliseconds. ​

• Heng Yang and Luca Carlone, In Perfect Shape: Certifiably Optimal 3D Shape Reconstruction from 2D Landmarks, In IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2020. —We present Shape*, the first certifiably optimal non-minimal solver for 3D shape reconstruction from 2D landmarks in a single image, and Shape#, a robust shape reconstruction algorithm that tolerates a large amount of outliers in the 2D measurements. We demonstrate the power of Sums-of-Squares (SOS) relaxations in solving challenging geometric perception.

• Heng Yang, Pasquale Antonante, Vasileios Tzoumas and Luca Carlone, Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejection, IEEE Robotics and Automation Letters (RA-L), 2020. (Video) Best Paper Award in Robot Vision at ICRA 2020, Best Paper Award Honorable Mention from RA-L 2020. —A general-purpose robust estimation framework called graduated non-convexity (GNC) that can be applied to any problem where a globally optimal non-minimal solver (e.g. from SDP and SOS relaxations) for the outlier-free case is available. Empirically robust againts 70-80% outliers across applications. As an alternative to RANSAC, GNC robustifies non-minimal solvers, while RANSAC robustifies minimal solvers.​

2019

• Heng Yang and Luca Carlone, A Quaternion-based Certifiably Optimal Solution to the Wahba Problem with Outliers, International Conference on Computer Vision (ICCV), 2019. Oral presentation (4% acceptance rate) (Video) —Introducing QUASAR (QUAternion-based Semidefinite relAxation for Robust alignment), a quaternion-based SDP relaxation that is tight and returns the certifiable global optima to the Wahba problem (aka rotation search) in the presence of large noise and 95% outliers.​

• Heng Yang and Luca Carlone, A Polynomial-time Solution for Robust Registration with Extreme Outlier Rates, Robotics: Science and Systems (RSS), 2019. Spotlight talk + Poster (Video) (Poster)—Introducing TEASER (Truncated least squares Estimation And SEmidefinite Relaxation), a robust point cloud registration algorithm that is robust against 99% outliers.

2018

• Heng Yang, Carolina Amador Carrascal, Hua Xie, Vijay Shamdasani and Brian W Anthony, Design and Experimental Validation of Miniature External Mechanical Vibrators Towards Clinical Ultrasound Shear Wave Elastography. 2018 IEEE International Ultrasonics Symposium (IUS). — Enabling low-cost, miniature and portable ultrasound shear wave elastography imaging with external mechanical vibration.
• Felix Van De Donk, Heng Yang and Brian W Anthony, Miniaturization of external mechanical vibration for shear wave elastography imaging. 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). — Preliminary concept design of miniature external mechanical vibration device for portable ultrasound shear wave elastography imaging. 

2017

• Heng Yang, Man M Nguyen, Sheng-Wen Huang, Vijay Shamdasani, Hua Xie and Brian W Anthony, Simulation, design, and implementation of external mechanical vibration for ultrasound shear wave elastography. 2017 IEEE International Ultrasonics Symposium (IUS). — We propose to induce shear waves using a multi-point-source external mechanical vibration concept. Simulation and experimental prototype show promising results on liver phantoms.
• Julian Chacon-Castano, Daniel R Rathbone, Rachel Hoffman, Heng Yang, Dimitrios Pantazis, Jason Yang, Erik Hornberger and Nevan C Hanumara, Music and the brain-design of an MEG compatible piano. 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). — A piano design by optical fiber encoder that can be used in MEG room to study human brian activity induced by playing music.

2016

• Yiwei Zhao, Jianing Wu, Heng Yang and Shaoze Yan, The morphology and reciprocation movement of Honeybee's hairy tongue for nectar uptake. Journal of Bionic Engineering. 2016. 

2015

• Jianing Wu, Heng Yang and Shaoze Yan, Energy saving strategies of honeybees in dipping nectar. Scientific reports, 2015. — Through observing how honeybees drink, we get engineering insights of designing energy-saving micropumps.
• Zelin Linghu, Chenjia Zhao, Heng Yang and Xinqian Zheng, Beetle wing folding facilitated by micro-protrusions on the body surface: a case of Allomyrina dichotoma. Science bulletin, 2015. 

2014

• Heng Yang, Jianing Wu and Shaoze Yan, Effects of erectable glossal hairs on a honeybee's nectar-drinking strategy. Applied Physics Letters, 2014. — A mathematical model with delicate experimental observation that explains a very interesting phenomenon in nature: why all the flowers pollinated by honeybees have nectar concentration 35%? 

[Last edit: 07/16/2021]