Скачать или смотреть LiDAR-SLAM vs Other SLAM & Sensor Technologies

LiDAR-SLAM vs Other SLAM & Sensor Technologies

Research paper Title: A Comparative Survey of LiDAR-SLAM and LiDAR based Sensor Technologies
Presenter: Engr. Misha Urooj Khan (CERN , Switzerland)
🔗 Research Paper Link: https://ieeexplore.ieee.org/document/...
Conference Venue: IEEE MAJICC'21

This presentation explores the advancements in LiDAR-based SLAM (Simultaneous Localization and Mapping) and its crucial role in automation, robotics, autonomous vehicles, and smart cities. The research paper provides:
✅ A comparative analysis of LiDAR, Radar, UWB, and Wi-Fi sensor technologies
✅ An overview of LiDAR sensor classifications
✅ Mathematical & graphical modeling of LiDAR-SLAM
✅ Key SLAM features: Mapping, Localization, and Navigation
✅ A detailed comparison of LiDAR-SLAM vs. other SLAM approaches
✅ Insights into challenges & future research directions

In this video.
0:00 – Introduction & Greetings
0:19 – Research Paper & Co-Authors
0:40 – Presentation Roadmap: Outline: Motivation, LiDAR Sensors, SLAM Models, Challenges, Future Work.
0:54 – Motivation for SLAM in Robotics: Why Localization & Mapping are critical in Autonomous Robots.
1:31 – What is SLAM? (Simultaneous Localization and Mapping): History, EKF-based SLAM, and role in Robotics & Automation.
2:12 – Existing Localization Technologies Explained: GPS, IMU, GNSS, UWB, Wi-Fi – Advantages & Limitations.
4:06 – LiDAR Sensors Explained: Working principle, equations, and applications in Robotics & Smart Cities.
5:38 – 2D vs 3D LiDAR Sensor Technologies: Key differences, resolution, applications, and cost comparison.
6:22 – Mechanical LiDAR vs Solid-State LiDAR: Comparison of size, cost, performance, and future potential.
7:48 – LiDAR vs Other Positioning Systems: Comparison with Radar, UWB, Wi-Fi for Autonomous Navigation.
8:59 – Types of LiDAR Sensors: Airborne, Topographical, Terrestrial, Static, Solid-State, Mechanical.
9:55 – 2D LiDAR-SLAM Architecture: How 2D LiDAR-SLAM works for Mapping and Navigation.
10:36 – Mathematical Modeling of SLAM: Equations, Parameters & Probabilistic Models used in LiDAR-SLAM.
13:32 – Features of LiDAR-SLAM: Mapping, Localization, and Navigation in Robotics.
15:04 – LiDAR-SLAM vs Other SLAM Technologies: Comparison with EKF-SLAM, Fast-SLAM, Visual SLAM, ORB-SLAM, Graph-SLAM.
17:06 – Challenges in SLAM Implementation: Uncertainty, Data Association, Hardware Instability & Time Complexity.
21:00 – Conclusion & Future Work in LiDAR-SLAM: Findings, Applications, and Hybrid Approaches for Next-Gen Robotics.
22:54 – References & Research Sources
23:04 – Closing Remarks & Q/A

🔗 Follow us on Facebook: Community of Research and Development (CRD)   / community-of-research-and-development-crd-...  

If you are passionate about AI, Robotics, SLAM, and Sensor Technology, this research presentation is for you! 🌍✨

#LiDAR #SLAM #LiDARSensor #LiDARSLAM #AutonomousVehicles #Robotics #Mapping #Localization #Navigation #AI #ComputerVision #SensorTechnology #DeepLearning #Automation #SmartCities #3DRobotics #SelfDrivingCars #IEEE #Research #technology #mishauroojkhan #researchpedia #researchpublication