Update README.md

README.md

@@ -21,14 +21,11 @@ A library that deals with generalized quadratic pose estimation problems (QPEPs)
 ![alt tag](chart.png)
 
 # Authors
-Affiliation: **RAM-LAB**, Hong Kong University of Science and Technology (**HKUST**)
+Affiliation: Hong Kong University of Science and Technology (**HKUST**)
 
 Contributor: **Jin Wu** (https://github.com/zarathustr), jin_wu_uestc@hotmail.com
 
-Supervisor: **Prof. Ming Liu**, Dean of RAM-LAB, HKUST (https://ram-lab.com)
-
-Co-Contributors: **Xiangcheng Hu**, HKUST (https://github.com/JokerJohn), 
-**Heng Li**, Unity Drive Inc.
+Co-Contributor: **Xiangcheng Hu**, HKUST (https://github.com/JokerJohn)
 
 # Usage
 The C++ codes are built using ```CMake``` toolkit under the ```C++11``` programming standard. The codes have been verified on the ```Ubuntu 14.04/16.04/18.04``` (```GCC``` Compilers 5.0 ~ 10.0), Mac ```OS X 10.5.8/10.6.8/10.7.5/10.8.5/10.9.5/10.10/10.12/10.14/10.15``` (```Clang``` Compilers 3 ~ 11). We support multiple architectures, including x86, armhf, arm64, etc.
@@ -129,8 +126,8 @@ The usage of the theoretical proofs and mapping toolbox can be found in the supp
 The C++ version of LibQPEP originates from its MATLAB version codes in the ```code``` folder. To define a quadratic pose estimation problem (QPEP), we recommend that the problem can be written in the form of scalar objective function ```L``` such that the pose ```T``` on SE(3) is optimized via ```argmin J```, subject to the SO(3) constraints in ```T```. Then, please follow the ```syms*``` files in the root of MATLAB demo codes to generate the required numerical matrices for QPEP. After that, you may need to convert the matrices into C++ callable functions. Please refer to ```misc_*_funcs.cpp``` files for such a conversion. Finally, you may solve the problem via the provided solvers. If one needs the covariance estimation, please follow the steps in ```main.cpp```, where an example of the covariance estimation of point-to-plane registration has been presented. We expect that more problems can be solved in the QPEP fashion!
 
 # References
-1. **Wu, J.**, Zheng, Y., Gao, Z., Jiang, Y., Hu, X., Zhu, Y., Jiao, J., **Liu, M.** (2022)
+1. **Wu, J.**, et al. (2022)
            Quadratic Pose Estimation Problems: Globally Optimal Solutions, 
            Solvability/Observability Analysis and Uncertainty Description, ***IEEE Transactions on Robotics***, https://doi.org/10.1109/TRO.2022.3155880.
 
-2. **Wu, J.**, **Liu, M.**, Zhu, Y., Zou, Z., Dai, M.-Z., Zhang, C., Jiang, Y., Li, C. (2020). Globally Optimal Symbolic Hand-Eye Calibration. ***IEEE/ASME Transactions on Mechatronics***, https://doi.org/10.1109/TMECH.2020.3019306
+2. **Wu, J.**, et al. (2020). Globally Optimal Symbolic Hand-Eye Calibration. ***IEEE/ASME Transactions on Mechatronics***, https://doi.org/10.1109/TMECH.2020.3019306