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An Integrated INS/LiDAR SLAM Navigation System for GNSS-Challenging Environments
Nader Abdelaziz1,2, Ahmed El-Rabbany1
1Department of Civil Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada.
Sensors (Basel, Switzerland)
|June 24, 2022
Summary
This study integrates inertial navigation systems (INS) with LiDAR simultaneous mapping and localization (SLAM) to improve navigation accuracy during GPS outages. The combined system significantly reduces positioning errors compared to INS alone.
Area of Science:
- Robotics
- Navigation Systems
- Sensor Fusion
Background:
- Traditional navigation relies on Global Navigation Satellite System (GNSS)/inertial navigation system (INS) integration.
- Prolonged GNSS outages lead to significant INS drift, necessitating additional sensor integration.
Purpose of the Study:
- To propose and evaluate a robust loosely coupled (LC) integration of INS and LiDAR SLAM.
- To enhance navigation system performance during GNSS signal unavailability.
Main Methods:
- Utilized an extended Kalman filter (EKF) for INS and LiDAR SLAM loosely coupled integration.
- Tested the system on the KITTI dataset across residential and highway driving scenarios.
- Simulated complete GNSS absence and intermittent GNSS signal availability.
Main Results:
- The INS/LiDAR SLAM system demonstrated superior performance over standalone INS.
- Achieved an 88% and 32% reduction in horizontal and up direction Root Mean Square Error (RMSE) on residential datasets.
- Reported 70% and 0.2% RMSE reductions for horizontal and up directions on highway datasets.
Conclusions:
- The proposed INS/LiDAR SLAM integration offers a robust solution for navigation during GNSS outages.
- LiDAR SLAM effectively compensates for INS drift, improving overall positioning accuracy.
- The system shows promise for real-world applications requiring reliable navigation in GNSS-denied environments.
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