Search results: Found 3

Listing 1 - 3 of 3
Sort by
Lane-Precise Localization with Production Vehicle Sensors and Application to Augmented Reality Navigation

Author:
Book Series: Schriftenreihe / Institut für Mess- und Regelungstechnik, Karlsruher Institut für Technologie ISSN: 16134214 ISBN: 9783731508540 Year: Volume: 042 Pages: XII, 165 p. DOI: 10.5445/KSP/1000086154 Language: ENGLISH
Publisher: KIT Scientific Publishing
Subject: Technology (General)
Added to DOAB on : 2019-07-28 18:37:01
License:

Loading...
Export citation

Choose an application

Abstract

This works describes an approach to lane-precise localization on current digital maps. A particle filter fuses data from production vehicle sensors, such as GPS, radar, and camera. Performance evaluations on more than 200 km of data show that the proposed algorithm can reliably determine the current lane. Furthermore, a possible architecture for an intuitive route guidance system based on Augmented Reality is proposed together with a lane-change recommendation for unclear situations.

Selected Papers from 2017 International Conference on Micro/Nanomachines

Authors: ---
ISBN: 9783038970811 9783038970828 Year: Pages: VIII, 170 DOI: 10.3390/books978-3-03897-082-8 Language: english
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Sciences --- Mechanical Engineering
Added to DOAB on : 2018-08-09 17:08:18
License:

Loading...
Export citation

Choose an application

Abstract

The 2017 International Conference on Micro/Nanomachines (http://www.icmnm.org/) was held in Wuhan, China, 25–28 August, 2017. Micro/nanomotors (MNMs), which are defined as micro/nanodevices capable of converting energy into autonomous motion, can be used to pick up, transport, and release various cargoes within a liquid medium. They have important potential applications, for example, in drug delivery, biosensors, protein and cell separation, microsurgeries, and environment remediation. MNMs can be classified into two categories, according to their propulsion mechanism. In this respect, self-propelled MNMs are capable of moving autonomously without external intervention, but they either require toxic fuel or have a short lifespan. MNMs actuated by external fields, such as light, magnetic field, and acoustic waves, are not subject to these problems, do not require toxic fuels, nor give rise to by-products during the motion process. For both self-propelled and field-actuated MNMs, there is still a long way to go before we reach practical applications. The future development of MNMs should be focused on improving the energy conversion efficiency through structure optimization, exploring new propulsion mechanisms and endowing MNMs with environmental responses for self-navigation, detection, and specific operations. In this way, MNMs will approach their practical application in biomedicine, environment treatment, microengineering, etc.

Image Processing in Agriculture and Forestry

Authors: ---
ISBN: 9783038970972 9783038970989 Year: Pages: 222 DOI: 10.3390/books978-3-03897-098-9 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Mechanical Engineering
Added to DOAB on : 2018-09-27 09:15:10
License:

Loading...
Export citation

Choose an application

Abstract

Image processing in agriculture and forestry represents a challenge towards the automation of tasks for better performances. Agronomists, computer and robotics engineers, and agricultural machinery industry manufacturers now have at their disposal a book containing a collection of methods, procedures, designs, and descriptions at the technological forefront, which serves as an important support and aid for the implementation and development of their own ideas.The book describes: (1) Applications (canopy on trees, aboveground biomass, phenotyping, chlorophyll, leaf area index, water and nutrient content, land cover change, soil properties, and secure autonomous navigation); (2) Imaging devices onboard robots, unmanned aerial vehicles (UAVs), and satellites operating at different spectral ranges (visible, infrared, hyper-multispectral bands, and radar), as well as guidelines for selecting machine vision systems in outdoor environments; and (3) (Specific computer vision methods (generic and convolutional neural networks, machine learning, specific segmentation approaches, vegetation indices, and three-dimensional (3D) reconstruction).

Listing 1 - 3 of 3
Sort by
Narrow your search