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Guidance system

About: Guidance system is a research topic. Over the lifetime, 4282 publications have been published within this topic receiving 45964 citations.


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Journal ArticleDOI
TL;DR: In this article, a fuzzy logic enhanced Kalman filter was developed to fuse the information from machine vision, laser radar, IMU, and speed sensor for guiding an autonomous vehicle through citrus grove alleyways.
Abstract: This article discusses the development of a sensor fusion system for guiding an autonomous vehicle through citrus grove alleyways. The sensor system for path finding consists of machine vision and laser radar. An inertial measurement unit (IMU) is used for detecting the tilt of the vehicle, and a speed sensor is used to find the travel speed. A fuzzy logic enhanced Kalman filter was developed to fuse the information from machine vision, laser radar, IMU, and speed sensor. The fused information is used to guide a vehicle. The algorithm was simulated and then implemented on a tractor guidance system. The guidance system's ability to navigate the vehicle at the middle of the path was first tested in a test path. Average errors of 1.9 cm at 3.1 m s -1 and 1.5 cm at 1.8 m s -1 were observed in the tests. A comparison was made between guiding the vehicle using the sensors independently and using fusion. Guidance based on sensor fusion was found to be more accurate than guidance using independent sensors. The guidance system was then tested in citrus grove alleyways, and average errors of 7.6 cm at 3.1 m s -1 and 9.1 cm at 1.8 m s -1 were observed. Visually, the navigation in the citrus grove alleyway was as good

59 citations

Proceedings ArticleDOI
01 Jul 2007
TL;DR: The potential to design an application for the visually impaired even when to- date 'positioning and tracking' system cannot offer reliable position information that highly required by this type of application is explored.
Abstract: This paper describes, path planning and following algorithms for use in indoor navigation for the blind and visually impaired. Providing indoor navigational assistance for this type of users presents additional challenges not faced by conventional guidance systems, due to the personal nature of the interactions. The algorithms are part of an overall Indoor Navigation Model that is used to provide assistance and guidance in unfamiliar indoor environments. Path planning uses the A* and Dijkstra's shortest path algorithms, to operate on an "Intelligent Map", that is based on a new data structure termed "cactus tree" which is predicated on the relationships between the different objects that represent an indoor environment. The paths produced are termed "virtual hand rails", which can be used to dynamically plan a path for a user within a region. The path following algorithm is based on dead reckoning, but incorporates human factors as well as information about the flooring and furnishing structures along the intended planned path. Experimental and simulating results show that the guiding/navigation problem becomes a divergent mathematical problem if the positional information offered by the positioning and tracking systems does not reach a certain requirement. This research explores the potential to design an application for the visually impaired even when to- date 'positioning and tracking' system cannot offer reliable position information that highly required by this type of application.

59 citations

Journal ArticleDOI
TL;DR: In this paper, a two-dimensional path following control system for autonomous surface vehicles is presented through a way-point guidance scheme based on a vector field algorithm, which is a simple and robust method and its stability is proved using Lyapunov stability criteria.

59 citations

01 Jan 1993
TL;DR: In this article, the authors describe driver performance and behavior when using an in-vehicle route guidance system, and a manually dialed car phone, and provide normative data for driving without use of an in vehicle information system.
Abstract: This report describes driver performance and behavior when using an in- vehicle route guidance system, and a manually dialed car phone. It also provides normative data for driving without use of an in- vehicle information system. Description of the route guidance system and drivers' preferences, are also included.

58 citations

Journal ArticleDOI
TL;DR: Investigations are reported about investigations to combine passive GPS- and map-based route guidance with model-based machine vision in order to automatically assess or even execute driving maneuvers in inner-city traffic situations.
Abstract: Currently available driver assistance systems (i) warn the driver based on vehicle state sensors (e.g., door open, outside temperature near or below the freezing point), (ii) offer route guidance information (navigation systems based on GPS and digital road maps), or—in some critical situations—(iii) even actively influence vehicle handling under carefully delimited conditions (anti-blocking-system, electronic-stability-program). This contribution reports about investigations to combine passive GPS- and map-based route guidance with model-based machine vision in order to automatically assess or even execute driving maneuvers in inner-city traffic situations. Information provided by todays route guidance systems is treated as a generic description of lane structure. The schematic description of lane structures extractable from commercially available standard digital maps is automatically instantiated by a machine vision approach which interprets video image sequences recorded by cameras from within a driving vehicle. The resulting model of the lane structure in front of the vehicle is subsequently exploited in order to control vehicle maneuvers in real-time as a proof of principal system competences. The machine-vision-based execution of driving maneuvers can at any time be overridden by the driver.

58 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202319
202252
202197
2020141
2019194
2018206