SLAM 3D‑Mapping Algorithm Engineer (Negative‑Pressure Wall‑Climbing Robot)

Job Responsibilities

1. Research, optimize and implement core SLAM 3D‑mapping algorithms for negative‑pressure wall‑climbing robots. Adapt algorithms for tracked/wheeled locomotion scenarios, and resolve challenges of mapping accuracy and real‑time performance in complex environments.
2. Lead the design of multi‑sensor fusion algorithms for IMU, LiDAR, stereo cameras and encoders. Optimize strategies for data synchronization, noise reduction and sensor complementarity to improve the robustness and positioning accuracy of the SLAM system.
3. Integrate and debug SLAM algorithms with the ROS2 system, collaborate with the ROS2 embedded software team to realize algorithm engineering deployment, performance tuning and troubleshooting.
4. Keep track of cutting‑edge SLAM technologies (Semantic SLAM, Dynamic SLAM). Propose, implement and verify technical improvement solutions tailored to real‑world application scenarios of wall‑climbing robots.
5. Compile algorithm design documents and test reports. Participate in standardizing algorithm R&D workflows within the R&D center, and provide technical guidance for junior algorithm engineers.

Job Requirements

1. Education: Bachelor’s degree or above in Computer Science, Automation, Robotics, Artificial Intelligence or related fields. Minimum 2‑years hands‑on experience in SLAM algorithm R&D; proven experience in deploying robot SLAM systems is preferred.
2. Core Skills: Proficient in C/C++ and Python; experienced with ROS2; in‑depth understanding of SLAM fundamentals; familiar with mainstream SLAM frameworks including Cartographer, LOAM series and GMapping.
3. Must‑have Experience: Practical experience in multi‑sensor fusion mapping with IMU, LiDAR and cameras. Solid knowledge of fusion algorithms such as Kalman Filter and Particle Filter; capable of algorithm simulation using MATLAB/Simulink.
4. Additional Competencies: Understanding of tracked/wheeled robot locomotion characteristics; prior experience optimizing SLAM algorithms for complex environments is preferred. Strong logical thinking and troubleshooting capabilities.
5. Soft Skills: Excellent communication, teamwork and technical documentation skills. Capable of conducting joint system debugging with software and hardware teams, and align with the technical philosophy of the R&D center.