视觉SLAM导航

1、负责基于视觉（单目/双目/RGB-D）或多传感器融合的SLAM算法开发与优化，实现高精度的实时定位与建图。

2、设计并实现机器人/无人系统的自主导航算法（路径规划、避障、运动控制等），结合SLAM结果完成动态环境下的鲁棒导航。

3、优化算法性能（速度、精度、鲁棒性），解决实际场景中的光照变化、动态物体、纹理缺失等问题。

4、参与传感器标定、多传感器（IMU、激光雷达、视觉等）时间同步与数据融合。

5、部署算法到嵌入式平台（如ROS、ARM、Jetson等），完成硬件适配与性能调优。

6、撰写技术文档，参与算法模块的测试、验证与落地应用。

Job Description:

1. Develop and optimize vision-based (monocular/binocular/RGB-D) or multi-sensor fusion SLAM algorithms for high-precision real-time localization and mapping.

2. Design autonomous navigation algorithms (path planning, obstacle avoidance, motion control) for robots/unmanned systems, enabling robust navigation in dynamic environments with SLAM integration.

3. Optimize algorithm performance (speed, accuracy, robustness) to address illumination changes, dynamic objects, texture loss in real scenarios.

4. Participate in sensor calibration, time synchronization and data fusion for multi-sensors (IMU, LiDAR, vision, etc.).

5. Deploy algorithms to embedded platforms (ROS, ARM, Jetson, etc.) for hardware adaptation and performance tuning.

6. Write technical documents and participate in testing, verification and application of algorithm modules.

任职要求：

1、硕士及以上学历，计算机、机器人、自动化、电子工程等相关专业。

2、精通视觉SLAM算法（如ORB-SLAM、VINS-Fusion、LSD-SLAM等），熟悉特征提取、BA优化、闭环检测等关键技术。

3、熟悉导航相关算法（A、D、RRT、动态窗口法DWA等），有实际路径规划与避障项目经验。

4、熟练掌握C++/Python，熟悉Linux开发环境，有ROS框架使用经验。

5、熟悉多传感器融合（视觉+IMU/激光雷达）及滤波算法（EKF、粒子滤波、图优化等）。

Job Requirement:

1. Master's degree or above in Computer Science, Robotics, Automation, Electronic Engineering or related majors.

2. Proficient in visual SLAM algorithms (e.g., ORB-SLAM, VINS-Fusion, LSD-SLAM) and key technologies including feature extraction, BA optimization, loop closure detection.

3. Familiar with navigation algorithms (A*, D*, RRT, DWA, etc.) and with practical experience in path planning and obstacle avoidance projects.

4. Proficiency in C++/Python, familiar with Linux development environment and experienced in using ROS framework.

5. Familiar with multi-sensor fusion (vision + IMU/LiDAR) and filtering algorithms (EKF, particle filter, graph optimization, etc.).