Pixel-Based Range Processing for Autonomous Driving

We describe a pixel-based approach to range processing for obstacle detection and autonomous driving as an alternative to the traditional image- or map-based approaches. The pixel-based approach eliminates the delays due to image acquisition and map building and permits the integration of traversability evaluation and path generation into a single module without the latency involved in distributed systems. We describe the algorithm used for updating a local map using individual range pixels, for detecting obstacles on the fly, and for generating steering commands. We illustrate the performance of the algorithm using an implementation of a cross-country driving system with a scanning laser range finder