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This article presents a robust approach to navigating at high-speed across desert terrain. A central theme of this approach is the combination of simple ideas and components to build a capable and robust system. A pair of robots were developed which completed a 212 kilometer Grand Challenge desert race in approximately seven hours. A path-centric navigation system uses a combination of LIDAR and RADAR...
Boss is an autonomous vehicle that uses on-board sensors (GPS, lasers, radars, and cameras) to track other vehicles, detect static obstacles and localize itself relative to a road model. A three-layer planning system combines mission, behavioral and motion planning to drive in urban environments. The mission planning layer considers which street to take to achieve a mission goal. The behavioral layer...
The outdoor perception problem is a major challenge for driver-assistance and autonomous vehicle systems. While these systems can often employ active sensors such as sonar, radar, and lidar to perceive their surroundings, the state of standard traffic lights can only be perceived visually. By using a prior map, a perception system can anticipate and predict the locations of traffic lights and improve...
We present a motion planner for autonomous highway driving that adapts the state lattice framework pioneered for planetary rover navigation to the structured environment of public roadways. The main contribution of this paper is a search space representation that allows the search algorithm to systematically and efficiently explore both spatial and temporal dimensions in real time. This allows the...
The Urban Challenge was a robotic vehicle race through a simulated urban environment. Full size autonomous vehicles were required to complete a 60 mile course, while independently reasoning about other autonomous and human driven vehicles. The vehicles were required to safely handle intersections, multi-lane roads, parking lots and unusual situations. Teams from around the world attempted the competition...
This paper presents an approach that achieves robust high-speed navigation of prescribed routes. We present the mechatronic and software considerations that resulted in two robots that have completed over 4000 km of autonomous navigation of trails and off-road terrain at an average speed of approximately 30 km/h, with sustained top speeds of 55 km/h
The 2005 DARPA Grand Challenge, a 212-kilometer race through the Mojave Desert, showcased the state of the art in high-speed, autonomous navigation of trails and roads. To win the challenge, a team's robot had to complete the course faster than any other robot, and it had to do so within 10 hours. Carnegie Mellon University's Red Team developed two robots, which used a combination of autonomous and...
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