[3D-DLAD-v4] Strategies and methods for automotive sensor fusion, Robert Laganiere

3D-DLAD-v4 Workshop
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Speaker : Robert Laganiere, Professor University of Ottawa, CEO Sensor Cortek
Abstract : The development of road vehicles with a high level of autonomy requires advanced perception capabilities. These vehicles are generally equipped with three main sensor types: cameras, lidar and radar. However, the intrinsic limitation of each sensor affects the performance of the perception task. One way to overcome this issue and to increase the overall performance is to combine the information coming from different sensor modalities. This is the objective of sensor fusion to combine the information coming from different sensors and thus improve the perceptual ability of the vehicle. This way the vehicle can better operate under challenging environmental conditions by relying on the sensor data that is the least impacted by the current situation (e.g. poor lighting, adverse weather). In this presentation, we will present the main sensor fusion strategies that can be used for combining heterogeneous sensor data. In particular, we will discuss the three main fusion methods that can be applied in a perception system, namely early fusion, late fusion and mid-level fusion.