Experience

Black Sesame Technologies Inc

• United States
• Technology, Information and Internet
• 1 - 100 Employee

• Software Engineer, perception

  • Nov 2020 - Present

  Santa Clara County, California, United States



University of Michigan

• United States
• Higher Education
• 700 & Above Employee

• Research Assistant

  • Sep 2019 - Nov 2020

  Ann Arbor, MI, US



MoonX.ai

• Software Engineer Intern - SLAM

  • Jun 2019 - Aug 2019

  Shenzhen, Guangdong, China (c++) Developed a 3D HD map creation algorithm based on graph-based SLAM algorithm (Simultaneous Localization and Mapping with graph optimization). • Designed a submap forming method to simplify the calculation unit from point-cloud to submap. Designed an adaptive trigger based on LiDar covariance for the execution of submap forming. Increased the map creation speed by 20%. • Implemented Boost RTree algorithm to find loop-closure. Improved the RMSE by 18% compared to KdTree… Show more (c++) Developed a 3D HD map creation algorithm based on graph-based SLAM algorithm (Simultaneous Localization and Mapping with graph optimization). • Designed a submap forming method to simplify the calculation unit from point-cloud to submap. Designed an adaptive trigger based on LiDar covariance for the execution of submap forming. Increased the map creation speed by 20%. • Implemented Boost RTree algorithm to find loop-closure. Improved the RMSE by 18% compared to KdTree algorithm. • Designed an outlier remover to check the global consistency of every loop-closure finding based on chi-square test. • Utilized Google Protocol Buffer to serialize point-cloud pose related data. Speed up the data processing. Show less



University of Michigan

• United States
• Higher Education
• 700 & Above Employee

• Research Assistant

  • Jan 2019 - May 2019

  Ann Arbor, MI (MATLAB) Presented a VO method (Visual Odometry, algorithms estimating the robot state with vision information) based on direct intensity from RGB-D image. • Implemented Gauss-Newton algorithm to solve the optimal transformation between frames by minimizing the intensity residual from all pixels. Increased the reliability of registration when camera distort/defocus. • Adopted a sliding window optimization to process frames in batch. Realized a semi-global pose synchronization. •… Show more (MATLAB) Presented a VO method (Visual Odometry, algorithms estimating the robot state with vision information) based on direct intensity from RGB-D image. • Implemented Gauss-Newton algorithm to solve the optimal transformation between frames by minimizing the intensity residual from all pixels. Increased the reliability of registration when camera distort/defocus. • Adopted a sliding window optimization to process frames in batch. Realized a semi-global pose synchronization. • Developed a coarse-to-fine data scheme to reduce the computation load in large camera motions (x2 speed up). Show less