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Smart Sensor Fusion for Autonomous Systems

The smart sensor fusion system presents an innovative theoretical framework covering intelligent data fusion algorithms in detection, measurement and object levels using emerging signal processing theory, estimation theory and situation analysis approaches.

The multi-modality data from radar, lidar, and camera are properly processed, enabling high fidelity environment digitalization and comprehensive scene understanding. The resulting world model facilitates follow-up trajectory planning and adaptive control for real world autonomy.

The smart sensor fusion driven vehicles can operate autonomously with instant recognition and response to the surroundings in complicated environments at all weather conditions, in particular, using an adaptive mechanism to select the optimal data processing and fusion approaches in real time.

Events

  • Message from the Chief Editor of Professor Cai Yunze

    2023/10

    Journal of Shanghai Jiao Tong University (Science) is committed to publishing rich research results in interdisciplinary fields.

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  • Anders Lindquist spoke at WDCC 2023

    2023/10

    The 2023 World Design Capital Conference hosted by the Shanghai Municipal Government will kick off at the Huangpu Riverside in Shanghai from September 26 to October 2. Academicians and top experts at home and abroad are invited to conduct multi-disciplinary collisions and in-depth discussions on design as the engine of change for future human settlements from multiple angles.

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Events
Events

  • Shenzhen Airport's Kind Visit to Our Lab

    2023/08

    Leaders of Shenzhen Airport and Weihai Guangtai visit sjtu with Director Ting Yuan...

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  • JAIF Special Issue on Automotive Radar Perception Systems

    2022/01

    Autonomous driving (AD) poses unique challenges for vehicle environment perception system in complicated driving scenarios. Automotive radar systems, along with lidar and camera systems, are a major perception tool for driverless automation. Automotive radar has already existed as a must-have component in many advanced driver assistant systems (ADAS) and nowadays AD systems have a higher requirement for radar sensors to provide imaging like capabilities and carry out more comprehensive perception tasks. There are two major technical lessons learned in recently years on automotive radar systems for vehicle intelligence

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  • Autonomy on Logistics and Heavy Machinery

    2023/01

    Director Ting Yuan discuss prospect of Autonomy on Logistics with Xinda Stock.

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