Navigation - NAVI002 - Adaptive Hybrid Navigation for Autonomous Mobile Robots in GPS-Denied Environments

Track: NAVIGATION.

Project: Develop a hybrid navigation system capable of operating with and without GPS/GNSS availability by combining satellite‑based positioning with onboard localization techniques (sensor fusion).

Objective:

• Seamlessly navigate between GPS‑assisted and GPS‑denied modes.
• Fuse GPS/GNSS with LiDAR, IMU, and camera‑based localization (e.g., visual odometry).
• Detect GPS degradation/loss, automatically switch to an alternative localization strategy, and maintain accurate positioning and autonomous navigation until GPS is restored.

Required skills:

• Proficiency in Python and C++.
• Experience with ROS 2.
• Knowledge of autonomous navigation and localization; understanding of sensor fusion and coordinate transformations.

Recommended skills:

• Familiarity with GPS/GNSS, LiDAR, IMU, and camera‑based perception; SLAM, visual and LiDAR odometry; Nav2 and localization algorithms; Kalman Filters (EKF/UKF); Gazebo or other robotics simulators.

Application: Email only. Include the subject reference in the email subject and attach your CV and cover letter. Any other method is not considered.