Radar and Vision Sensor Fusion for Object Detection in Autonomous Vehicle Surroundings

Multi-sensor data fusion for advanced driver assistance systems (ADAS) in the automotive industry has received much attention recently due to the emergence of self-driving vehicles and road traffic safety applications. Accurate surroundings recognition through sensors is critical to achieving efficient advanced driver assistance systems (ADAS). In this paper, we use radar and vision sensors for accurate object recognition. However, since sensor-specific data have different coordinates, the data coordinate calibrate is essential. In this paper, we introduce the coordinate calibration algorithms between radar and vision images and perform sensor calibrating using data obtained from actual sensors.