<p>Duties include:</p>
<p>Responsible for the development and optimization of robot laser SLAM algorithms, including mapping, localization, closed-loop detection, path planning, etc. core modules<br>Research multi-sensor fusion technology (laser radar, IMU, odometer, vision, etc.), improve the algorithm's robustness and accuracy in dynamic environments<br>Optimize algorithm performance for indoor and outdoor complex scenes (such as warehouses, industries, service robots, etc.), and complete the transplantation and deployment of embedded platforms<br>Collaborate with the hardware team to complete sensor calibration, system integration and field testing, and solve technical problems in actual applications<br>Write algorithm design documents, test reports and technical solutions to support product iteration and intellectual property applications<br>Collaborate with product and testing teams to push algorithms into practical application in robot navigation systems<br>Job Requirements</p>
<p>Bachelor's degree or above, majoring in Computer Science, Automation, Robotics, Electronic Engineering, etc. <br>3 years of laser SLAM algorithm development experience, familiar with mainstream frameworks such as Cartographer, Gmapping, LOAM, etc.<br>Proficient in C++/Python programming, familiar with Linux/ROS development environment, and familiar with Eigen, PCL, Ceres, g2o, etc. algorithm libraries<br>Solid mathematical foundation (probability theory, linear algebra, graph optimization, etc.), able to independently derive SLAM-related mathematical models<br><br>Have practical experience in multi-sensor calibration, point cloud processing, real-time system optimization, etc.<br>Priority conditions</p>
<p>Familiar with visual SLAM (such as ORB-SLAM, VINS-Fusion) or semantic SLAM technology<br>Experience in algorithm transplantation to embedded platforms (such as ARM, STM32)<br>Participated in robot competitions or published related field papers/patents<br>English can be used as a working language</p>