Using stereo vision on a fast moving unmanned ground vehicle


To develop visual SLAM, obstacle detection and tracking as well as road feature detection system for a high-speed unmanned ground vehicle using real-time stereo vision.


The focus of this project is on developing computationally efficient algorithms that support obstacle detection and terrain classification using stereo vision techniques. The development of long-range advanced stereo vision techniques, as compared to other techniques that depend on active vision i.e. lidar, enables low-cost implementation of obstacle detection and collision avoidance for autonomous vehicles. The stereovision system aims to achieve both distant object detection up to 50m and robust localisation at a maximum speed of 50 km/h.


                                                                             Lane detection


                                                       Detection and segmentation of obstacle up to 50m.

                                                          Real-time loop closure scenario at 50 km/h

Principal Investigators

Associate Prof. Wang Han (NTU)

Telephone: 6790 4506
Office: S2-B2b-49
Mr. Paul Tan (STE)

Telephone: 6660 1052
Office: S1-B4a-03