Navigation Algorithm Engineer

1 day ago


hong kong, Hong Kong SAR China Hong Kong Center for Construction Robotics Full time

5 days ago Be among the first 25 applicants 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. 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. Seniority level: Associate Employment type: Full‑time Job function: Engineering and Engineering #J-18808-Ljbffr



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