LIDAR-IMU sensor fusion based localization for autonomous mobile robot
Autonomous Mobile Robots (AMR) has taken a pivotal role in the revolutionizing of Industries. One of the key component of Autonomy for the AMR is the ability to perceive its environment and its location in it. Along with precise sensors, high-speed connectivity and advances in computational abiliti...
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| Format: | Final Year Project |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/177851 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | Autonomous Mobile Robots (AMR) has taken a pivotal role in the revolutionizing of Industries. One of the key component of Autonomy for the AMR is the ability to perceive its environment and its location in it. Along with precise sensors, high-speed connectivity and advances in computational abilities, Simultaneous Localization and Mapping (SLAM) Algorithms play are essential in order to make AMRs truly autonomous. In this report to explore the journey of development of SLAM Algorithms from its inception in 1980s to the present day. This report has 4 key results, discussions and contributions:
1. Experiments and Discussion on Rao-Blackwellized Particle Filter based SLAM.
2. Results and Discussion on Adversarial Training for Vision Models for better robustness against natural adversaries for feature detection.
3. Results and Discussion on comparison of LiDAR vs LiDAR-IMU based SLAM.
4. Experiments and Discussion on implementation of LiDAR-IMU based SLAM on physical AMR in RRC. |
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