A 2D/3D environment perception approach applied to sensor-based navigation of automated driving systems

The perception of the environment is one the most important tasks related to automated driving systems navigation. Typically, the robot detects the road surface and obstacles to perform the local navigation control safely. However, working with image data brings several problems related to environment elements like shadows, light reflection, low-variance textures, etc., which could compromise the efficiency of the final detection. We dealt with these problems in our previous work, where a 2D/3D image processing approach was proposed to detect the road surface. Although presenting good results, the final solution was time-consuming for a real application in autonomous navigation. Here, we propose some modifications in the 2D/3D structure to a better time efficient technique, allowing the road surface and obstacles detection. The final solution was tested successfully in a sensor-based navigation approach.