Topological large-scale off-road navigation and exploration RAVON at the European Land Robot Trial 2008

Braun, Tim; Schaefer, Heike; Berns, Karsten

doi:10.1109/iros.2009.5353985

Cited by 13 publications

(6 citation statements)

References 8 publications

(8 reference statements)

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“…Tests in competitive scenarios [2] validate the claim that the new, hybrid metrical/topological map structure indeed allows to perform cost-conscious path planning. At the same time, the robot does not need to construct a detailed metrical world model to reason about traversability costs.…”

Section: Resultsmentioning

confidence: 63%

Cost-Efficient Global Robot Navigation in Rugged Off-Road Terrain

Braun

2011

Künstl Intell

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The thesis "Cost-Efficient Global Robot Navigation in Rugged Off-Road Terrain" proposes a global robot navigation concept for rugged off-road terrain which is robust against inaccurate self-localization and scalable to large environments, but also cost-conscious, e.g. able to generate navigation paths which optimize a cost measure closely related to terrain traversability. The thesis contributes a set of new techniques to integrate costconsciousness into a primarily topological navigation scheme. Also, novel methods to learn and optimize cost estimates from experience are developed.

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Section: Resultsmentioning

confidence: 63%

Cost-Efficient Global Robot Navigation in Rugged Off-Road Terrain

Braun

2011

Künstl Intell

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“…The military themes included reconnaissance and surveillance, autonomous navigation, fleet transport and so on while civil scenes included safety, fire protection, and disaster control and so on. In the later tests, the autonomous cars and its task completion advanced year after year [8]. ELROB has played an active part in promoting the research of unmanned driving technologies in Europe [9].…”

Section: The Research Status Of Unmanned Driving Cars In Europementioning

confidence: 99%

A study on key technologies of unmanned driving

Zhang

Gao

Guo

et al. 2016

CAAI Transactions on Intelligence Technology

135

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Although the development of machine intelligence is far from simulating all the cognitive competence of our brains, still it is absolutely possible to peel the driving activity from people's cognitive activities and then make the machine finish some low-level, complicated and lasting driving cognition by simulating our brains. The goal of driving is to replace drivers and free them from boring driving activities. Based on some studies on unmanned driving, this paper summarizes and analyzes the background, significance, research status and key technology of unmanned driving and the research group also introduces some research on brain cognition of driving and sensor placement of intelligent vehicles, which offers more meaningful reference to push the study of unmanned driving.

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“…Competitions like the DARPA Grand Challenge 1 [100] or the European Robot Trial (ELROB 2 ) [16,25,42,56,57,61,91] have demonstrated the state of research in off-road robotics as well as the capabilities of various approaches and vehicles. Recently, the Learning Applied to Ground Robots (LAGR) project [52] of the DARPA has fostered the scientific progress in off-road robotics.…”

Section: Introductionmentioning

confidence: 99%