Robot Navigation Algorithm Engineer

Job Responsibilities

1. Responsible for the research, development, and optimization of robot laser SLAM algorithms, including core modules such as mapping, localization, loop closure detection, and path planning.
2. Research multi-sensor fusion technologies (LiDAR, IMU, odometry, vision, etc.) to improve the robustness and accuracy of algorithms in dynamic environments.
3. Optimize algorithm performance for complex indoor and outdoor scenarios (such as warehousing, industrial, and service robots), and complete migration and deployment on embedded platforms.
4. Collaborate with the hardware team to complete sensor calibration, system integration, and on-site testing, solving technical issues in practical applications.
5. Write algorithm design documents, test reports, and technical proposals, supporting product iterations and intellectual property applications.
6. Work with product and testing teams to promote the practical application of algorithms in robot navigation systems.

Job Requirements

1. Bachelor’s degree or above in Computer Science, Automation, Robotics, Electronic Engineering, or related fields.
2. Over 3 years of experience in laser SLAM algorithm development, familiar with mainstream frameworks such as Cartographer, Gmapping, LOAM, etc.
3. Proficient in C++/Python programming, familiar with Linux/ROS development environments, and skilled in using algorithm libraries such as Eigen, PCL, Ceres, g2o, etc.
4. Solid mathematical foundation (probability theory, linear algebra, graph optimization, etc.), able to independently derive SLAM-related mathematical models.
5. Familiar with the complete process of robot navigation (mapping, localization, path planning, obstacle avoidance); experience in AGV, sweeping robots, or autonomous driving is preferred.
6. Practical experience in multi-sensor calibration, point cloud processing, and real-time system optimization.

Preferred Qualifications

1. Familiar with 3D SLAM technology.
2. Experience in algorithm migration to embedded platforms (such as ARM, STM32).
3. Participation in robotics competitions or publication of papers/patents in related fields.
4. English proficiency sufficient for use as a working language.