Enhancing Autonomous Vehicle Navigation and Perception with Advanced Light Detection and Ranging (LiDAR) sensing Data Processing and Anomaly Detection Techniques

In this paper, we proposed a novel approach for improving autonomous vehicle (AV) navigation and perception using advanced LiDAR data processing and anomaly detection techniques. We improved anomaly detection in LiDAR data sequences using hierarchical probabilistic graphical models and a Markov Jump Particle Filter, enabling autonomous vehicles to navigate and perceive their surroundings with unprecedented accuracy. As a result of our method, anomalies are not only identified more effectively, but also spatial dynamics are better understood, enabling autonomous navigation to be significantly improved.