Vehicles capable of dynamic vision: a new breed of technical beings?
TLDR
‘4-D approach’ integrating expectation-based methods from systems dynamics and control engineering with methods from AI has allowed to create vehicles with unprecedented capabilities in the technical realm.About:
This article is published in Artificial Intelligence.The article was published on 1998-08-01 and is currently open access. It has received 78 citations till now.read more
Citations
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Patent
Vehicular vision system
Kenneth Schofield,Mark L. Larson +1 more
TL;DR: In this article, the camera is disposed at an interior portion of a vehicle equipped with the vehicular vision system, where the camera one of (i) views exterior of the equipped vehicle through the windshield of the vehicle and forward of the equipment and (ii) views from the windshield into the interior cabin of the equipments.
Journal ArticleDOI
Model based vehicle detection and tracking for autonomous urban driving
Anna Petrovskaya,Sebastian Thrun +1 more
TL;DR: The notion of motion evidence is presented, which allows us to overcome the low signal-to-noise ratio that arises during rapid detection of moving vehicles in noisy urban environments and how to detect poorly visible black vehicles.
Journal ArticleDOI
An Introduction to Inertial and Visual Sensing
TL;DR: In this article, the authors present a tutorial introduction to two important senses for biological and robotic systems -inertial and visual perception, and discuss the complementarity of these sensors, describe some fundamental approaches to fusing their outputs and survey the field.
Journal ArticleDOI
Vision and inertial sensor cooperation using gravity as a vertical reference
Jorge Lobo,Jorge Dias +1 more
TL;DR: A framework for using inertial sensor data in vision systems is set, some results obtained, and the unit sphere projection camera model is used, providing a simple model for inertial data integration.
Journal ArticleDOI
Automatic guidance for agricultural vehicles in Europe
R Keicher,H Seufert +1 more
TL;DR: In this article, an overview of guidance systems for agricultural vehicles or implements in Europe can be found, without claims to completeness, in the European Union, depending on who is funding the project, the systems range from a PC, with a frame grabber or a GNSS receiver used to guide an implement along a predefined path with speeds up to 3 m/s, to a multiprocessor bifocal road recognition system for autonomous cars driving on motorways with a speed of 130 km/h.
References
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Journal ArticleDOI
Observing the State of a Linear System
TL;DR: In this article, it was shown that the state vector of a linear system can be reconstructed from observations of the system inputs and outputs, and that the observer which reconstructs this state vector is itself a linear systems whose complexity decreases as the number of output quantities available increases.
Journal ArticleDOI
Recursive 3-D road and relative ego-state recognition
E.D. Dickmanns,B.D. Mysliwetz +1 more
TL;DR: The general problem of recognizing both horizontal and vertical road curvature parameters while driving along the road has been solved recursively and a differential geometry representation decoupled for the two curvature components has been selected.
Book
Neural Network Perception for Mobile Robot Guidance
TL;DR: This book describes a connectionist system called ALVINN (Autonomous Land Vehicle In a Neural Network) that overcomes difficulties and can learn to control an autonomous van in under 5 minutes by watching a person drive.
Journal ArticleDOI
Dynamic monocular machine vision
Ernst D. Dickmanns,Volker Graefe +1 more
TL;DR: A new approach to real-time machine vision in dynamic scenes is presented based on special hardware and methods for feature extraction and information processing using integral spatio-temporal models that by-passes the nonunique inversion of the perspective projection by applying recursive least squares filtering.
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