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WORKSHOP DETAILS

WS19: Cooperative Perception among Multiple Intelligent Vehicles

Workshop Code: y8dc2

Organizers

  • Zhe XuanYuan
    Affiliation: Beijing Normal University- Hong Kong Baptist University United International College, China
    E-mail: zhexuanyuan@uic.edu.hk

  • Long Chen
    Affiliation: Sun Yat-sen University, China
    E-mail: chenl46@mail.sysu.edu.cn

  • Kai Huang
    Affiliation: Sun Yat-sen University, China
    E-mail: huangk36@mail.sysu.edu.cn

Scope and Goals

Environment perception using different kinds of sensors is one of the most important tasks for intelligent vehicle systems. In order to make correct and precise decisions, the vehicles need to be aware of and understand the surroundings, such as maps, locations, other vehicles, pedestrians etc.

As a natural extension of perception system in single independent vehicles, cooperative perception among multiple intelligent vehicles has the potential to achieve a more effective, efficient and robust solution, because it has the apparent advantages of parallelism, distribution and redundancy.

However, the challenges are as evident. How to coordinate multiple intelligent vehicles? What information should be interchanged and in what format? What communication architecture should be used? Which tasks should be done locally and which remotely?

The special session aims to provide up-to-date research that could help advance understanding of the cooperative perception problem among multiple intelligent vehicles

Topics of Interest

  • Cooperative mapping and localization.
  • Cooperative object detection and tracking.
  • Reliable and efficient communication among multiple vehicles.
  • Sensor fusion techniques across multiple vehicles.
  • Distributed algorithm design and analysis for cooperative perception.
  • Multi-agent robotics theory and system.
  • Cooperative safety warning and blind spot identification.
  • Security issues regarding to cooperative perception.