Autonomous driving technology relies on the integration and fusion of data from multiple sensors to perceive the surrounding environment accurately. This presentation provides a concise overview of sensor fusion in autonomous driving systems, covering various essential aspects and AI methodologies employed in the process. Departing from a general overview of latest developments of sensor fusion and its role in autonomous driving, the session explores the application of Bayesian-based annotation systems in sensor fusion. The integration of AI concepts is another crucial topic addressed in this presentation. It highlights the role of AI at various stages of sensor fusion, including different ML approaches.
- Get a better sense of general sensor fusion and its flow
- Understand the stages involved in sensor fusion with examples
- Learn about the Bayesian based annotation system with examples
- Discover AI concepts in various stages of sensor fusion
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