RASCAL - an autonomous ground vehicle for desert driving in the DARPA grand challenge 2005

Abstract

The DARPA Grand Challenge is a competition of autonomous ground vehicles in the Mojave desert, with a prize of $2M for the winner. This event was organized in 2004 and will be held annually at least until 2007, until a team wins the prize. The teams are coming from various background, but the rule that no US government funding or technology that was created with US government funding could be used for this competition, prevented some of the well established players to participate. The team SciAutonics/Auburn-Engineering continues their effort to build a system for participation in this challenge, based on the 2004 entry RASCAL. The main focus in the system design is on improvements of the design from 2004. Novel sensing modalities the team plans to use in 2005, are a stereo vision system and a radar system for obstacle detection. Offline simulation allows to analyze situations in the laboratory and to replay recordings from sensors. The Grand Challenge 2005 will take place on October 8, and the SciAutonics/Auburn team intends to compete with the improved RASCAL system.

Cooperative Search and Survey Using Autonomous Underwater Vehicles (AUVs)

“…The works in [18] [19] studied movement assisted sensor deployment, [20] showed mobile sensor nodes increases the sensing coverage, and [21] studied a triangulation-based sensor coverage algorithm using three mobile sensor nodes. Individual mobile sensor node technologies such as AUVs [22], UAVs (Unmanned Aerial Vehicle) [23], and autonomous vehicles [24] also have been studied.…”

“…With these obtained values, the expected survey time of the fleet with a failure at level f can be calculated from (24).…”

Unmanned and autonomous ground vehicle

“…NI Vision Builder is used for automated inspection, gauging, part presence, guidance, and counting. This is external and independent application for building and machine vision application without the need for programming NI visionni Vision Assistant are the tools used in labview.NI Vision is used to create machine vision and scientific imaging applicationwhich helps for basic image analysis, image processing, and machine vision [15]. NI Vision tool helps to create image processing and machine vision applications.…”

Traversable terrain classification for outdoor autonomous robots using single 2D laser scans

“…Detection of borders or obstacles using laser scanners are often used both indoors and in populated outdoors environments, and is the favored method when the purpose includes map building, as in [5,8]. The Grand Challenge 2004 race demonstrated the difficulties in employing road following and obstacle avoidance for autonomous vehicles [1,12,17].…”