Hong Kong Center for Construction Robotics (HKCRC) is a scientific research and entrepreneurship platform established in 2020 by the Hong Kong University of Science and Technology and the University of California, Berkeley. It is affiliated with the Hong Kong government's InnoHK project. Led by Professor Li Zexiang, HKCRC aims to integrate advanced technologies like robotics, automation, and AI into the construction industry. The center focuses on research driven by real-world problems, engaging stakeholders, and fostering cross-team collaboration to deliver prototype solutions and startup teams for transformative changes in the construction sector. Their mission is to transform construction through technology by creating an open platform for industry partners, university researchers, and government organizations.
3D ScanningAIAutomationConstruction RoboticsEntrepreneurshipInnovationRobotics Platformhkcrc.hk
Hong Kong Center for Construction Robotics
Hong Kong Center for Construction Robotics (HKCRC) is a scientific research and entrepreneurship platform established in 2020 by the Hong Kong University of Science and Technology and the University of California, Berkeley. It is affiliated with the Hong Kong government's InnoHK project. Led by Professor Li Zexiang, HKCRC aims to integrate advanced technologies like robotics, automation, and AI into the construction industry. The center focuses on research driven by real-world problems, engaging stakeholders, and fostering cross-team collaboration to deliver prototype solutions and startup teams for transformative changes in the construction sector. Their mission is to transform construction through technology by creating an open platform for industry partners, university researchers, and government organizations.
3D ScanningAIAutomationConstruction RoboticsEntrepreneurshipInnovationRobotics Platformhkcrc.hk
HQHong Kong
Team Size44
Open Jobs12
Total Funding-
Latest FundraiseUnknown
Join the Team
Navigation Algorithm Engineer
On-SiteHong Kong
On-Site • Hong Kong
Job Responsibilities
Research and optimize laser SLAM algorithms for robots, including core modules such as mapping, localization, loop closure detection, and path planning.
Investigate multi-sensor fusion technologies (LiDAR, IMU, odometry, vision, etc.) to enhance algorithm robustness and accuracy in dynamic environments.
Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.
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Optimize algorithm performance for complex indoor and outdoor scenarios (e.g., warehousing, industrial, service robots) and complete porting and deployment on embedded platforms.
Collaborate with the hardware team to perform sensor calibration, system integration, and on-site testing, resolving technical challenges in real-world applications.
Write algorithm design documents, test reports, and technical solutions to support product iteration and intellectual property applications.
Work with product and testing teams to drive the practical implementation of algorithms in robot navigation systems.
Qualifications
Master's degree or higher in Computer Science, Automation, Robotics, Electrical Engineering, or related fields.
3+ years of experience in laser SLAM algorithm development, with familiarity in mainstream frameworks like Cartographer, Gmapping, and LOAM.
Proficient in C++/Python programming, experienced with Linux/ROS development environments, and skilled in using libraries such as Eigen, PCL, Ceres, and g2o.
Strong foundation in mathematics (probability theory, linear algebra, graph optimization, etc.), capable of independently deriving SLAM-related mathematical models.
Familiar with the full robot navigation process (mapping, localization, path planning, obstacle avoidance). Experience in AGV, robotic vacuum, or autonomous driving fields is a plus.
Hands-on experience in multi-sensor calibration, point cloud processing, and real-time system optimization.
