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.