INS/GPS/LiDAR Integrated Navigation System for Urban and Indoor Environments Using Hybrid Scan Matching Algorithm

Area of Science:

• Robotics and Autonomous Systems
• Geomatics Engineering
• Sensor Fusion

Background:

• Inertial Navigation Systems (INS) suffer from drift over time.
• Global Positioning System (GPS) offers global positioning but is susceptible to signal blockage.
• Light Detection and Ranging (LiDAR) provides precise relative positioning but lacks global referencing.

Purpose of the Study:

• To develop a robust multi-sensor navigation system combining GPS and LiDAR with INS.
• To enhance navigation accuracy and reliability across varied environmental conditions.
• To introduce a hybrid scan matching algorithm for improved performance.

Main Methods:

• Complementary integration of GPS and LiDAR with INS based on environmental conditions.
• Development of a hybrid scan matching algorithm merging feature-based and Iterative Closest Point (ICP) methods.
• Implementation and comparison of two INS-LiDAR integration schemes.

Main Results:

• The proposed system achieves sub-meter navigation accuracy throughout the trajectory.
• The hybrid scan matching algorithm demonstrates efficiency and robustness.
• Successful navigation demonstrated on an Unmanned Ground Vehicle (UGV) in both indoor and outdoor settings.

Conclusions:

• The multi-sensor integrated system effectively overcomes limitations of individual sensors.
• The hybrid approach provides reliable and accurate navigation in GPS-denied and open-sky environments.
• This research contributes to advancing autonomous navigation capabilities for UGVs.