VITS-A Vision System for Autonomous Land Vehicle Navigation
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special Issue on Industrial Machine Vision and Computer Vision Technology:8MPart
Rigid body motion from range image sequences
CVGIP: Image Understanding
Parallel Processing in the DARPA Strategic Computing Vision Program
IEEE Expert: Intelligent Systems and Their Applications
Techniques for Autonomous, Off-Road Navigation
IEEE Intelligent Systems
Toward Reliable Off Road Autonomous Vehicles Operating in Challenging Environments
International Journal of Robotics Research
Learning from Demonstration for Autonomous Navigation in Complex Unstructured Terrain
International Journal of Robotics Research
Terrain traversability analysis methods for unmanned ground vehicles: A survey
Engineering Applications of Artificial Intelligence
| Hi-index | 0.00 |
The development of a software system for obstacle avoidance that controls a vehicle smoothly, continuously, and safely across natural terrain en route to a goal is discussed. The work, carried out as part of the Strategic Computing Initiative of the US Defense Advanced Research Projects Agency (DARPA), was performed on the Autonomous Land Vehicle at Martin Marietta's Denver facilities. The planning software uses digital maps to plan a preferred route, and then, as the vehicle traverses that route, sensors are used to obtain scene descriptions. Techniques necessary to detect and avoid obstacles in cross-country terrain, with minimum delay between sensing and acting, are used. The system architecture, the cross-country perception system, the planning system for obstacle avoidance, the simulation environment, and the experiments are described. Work to develop a fine-grained control architecture, internalized plans, multisensor perception, and color image segmentation is discussed.