Vision Vehicles (131 results)

Condition: New.

Paperback or Softback. Condition: New. Vision-Aided, Cooperative Navigation for Multiple Unmanned Vehicles. Book.

Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

Condition: New. In English.

Paperback. Condition: Brand New. 1st edition. 88 pages. 9.00x6.00x0.20 inches. In Stock.

Paperback. Condition: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Condition: New.

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paperback. Condition: Very Good. Minor wear. Pages/covers clean.

Paperback or Softback. Condition: New. Applied Deep Learning and Computer Vision for Self-Driving Cars: Build autonomous vehicles using deep neural networks and behavior-cloning techniques. Book.

Condition: New.

Condition: New.

Condition: New. In English.

Condition: New. In English.

PF. Condition: New.

Condition: New.

Condition: New. pp. 332.

Condition: New. In English.

Condition: New. pp. 126.

Taschenbuch. Condition: Neu. Neuware - The motivation of this research is to exploit three attributes of increased unmanned vehicle use for intelligence, surveillance, and reconnaissance missions. These attributes are: increased numbers of unmanned vehicles, on-board vision, and wireless communications. The research begins with the development of a cooperative navigation system based on the measurement of vehicle position relative to shared landmark position estimates. Each vehicle in the network locates landmarks using it's on-board vision system and transmits the data to all other system vehicles. After receiving data from the other vehicles, the system fuses the landmarks with on-board measurements using a federated filter architecture. Simulations of the cooperative system, with and without ranging, are compared to a non-cooperative simulation. The comparison is performed using four platform motion scenarios: stationary, linear, angular, and full motion. The simulation results demonstrate position error estimate improvements of 0.5cm to 1cm. Additionally; the stationary and linear motion scenarios demonstrate attitude observability difficulties eliminated by the introduction of angular motion.This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work.This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.…

Paperback. Condition: Brand New. 114 pages. 8.75x6.00x0.25 inches. In Stock.

Paperback. Condition: New.

Condition: New. In English.

Condition: New. In English.

Paperback. Condition: New.

Condition: New. KlappentextrnrnThe motivation of this research is to exploit three attributes of increased unmanned vehicle use for intelligence, surveillance, and reconnaissance missions. These attributes are: increased numbers of unmanned vehicles, on-board v.

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Environment perception with cameras is an important requirement for many applications for autonomous vehicles and robots. This work presents a stereoscopic omnidirectional camera system for autonomous vehicles which resolves the problem of a limited field of view and provides a 360° panoramic view of the environment. We present a new projection model for these cameras and show that the camera setup overcomes major drawbacks of traditional perspective cameras in many applications.…