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Xiaoguang Dong Algorithm and application manager, ACEINNA |
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Biography Dong Xiaoguang has extensive experience in GNSS/INS algorithm development for autonomous systems. He currently manages a team of engineers for ACEINNA focused on delivering automotive and industrial inertial systems. His work and research has focused on IMU/GNSS fusion algorithms and real-world application development. He has a PhD in Aeronautical and Aerospace Science and Technology from Harbin Institute of Technology. Prior to ACEINNA, Dong’s research was centered around precision attitude determination and control system design with space vehicles. Abstract High-Integrity, Fault-Tolerant Open Inertial Measurement Platform for AI-based Vehicle Automation A rapidly growing application of AI+IoT technologies is autonomous vehicles. Autonomous vehicles from tiny drones to large freight trucks all require advanced sensor inputs to localize, perceive, and navigate the environment. At the same time the combination of AI and Sensing must provide safe, hazard-free operations in challenging environments. This talk will describe how Inertial Measurement Units (IMU) can be a key sensor to enable safe and reliable AI-based autonomous vehicles. The talk will also present a unique MEMS-based component architecture for an open, high-integrity, ISO26262 ASIL (Automotive Safety Integrity Level) compliant IMU platform that is both compact and high-performance. In addition, we will present how this component architecture can support the safety-compliant integration of additional advanced algorithms such as a Kalman Filter based GPS/INS sensor fusion algorithm directly on top of the IMU hardware processor minimizing overall system cost and size. |
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