LIDAR Autonomous Vehicles

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  One foggy night, a self-driving train was travelling in its usual course. Suddenly, one of its vision cameras was covered by a thin haze. That sensor had gone blind for a few moments, but the train did not swerve or brake. Rather, its radar and LiDAR replaced it, and the distance and hazard were analyzed perfectly. The expedition proceeded smoothly, and no one even guessed what actually happened. That smooth recovery is the strength of redundancy, enabled by advanced multimodal sensors. Understanding the Role of Redundancy Redundancy is the use of duplicate sensors to cross-check information. In case one sensor malfunctions, others replace it immediately. This idea is crucial in autonomous systems, where a fraction of a second's mistake can develop major hazards. With Multimodal Sensors , various sensing technologies such as LiDAR, radar, and cameras interchange their views, providing continuous operation in extreme conditions. Example: Cameras record in-depth ...