IEEE Organizations related to Unmanned Autonomous Vehicles

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No organizations are currently tagged "Unmanned Autonomous Vehicles"



Conferences related to Unmanned Autonomous Vehicles

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No conferences are currently tagged "Unmanned Autonomous Vehicles"


Periodicals related to Unmanned Autonomous Vehicles

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No periodicals are currently tagged "Unmanned Autonomous Vehicles"


Most published Xplore authors for Unmanned Autonomous Vehicles

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Xplore Articles related to Unmanned Autonomous Vehicles

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Taxis without drivers-or steering wheels

IEEE Spectrum, 2019

A COMING MILESTONE in the automobile world is the widespread rollout of Level 4 autonomy, where the car drives itself without supervision. Waymo, the company spun out of Google's self-driving car research, said it would start a commercial Level 4 taxi service by late 2018, although that hadn't happened as of press time. And GM Cruise, in San Francisco, is ...


Expanding the Design Horizon for Self-Driving Vehicles: Distributing Benefits and Burdens

IEEE Technology and Society Magazine, 2016

With over one billion vehicles in the world today, the motorized road vehicle is the pillar of modern society. Since the beginning of the 20th century, the automobile has revolutionized our spaces, practices, cultures, and identities through a complex matrix of technical, financial, economic, political, and social linkages. Visions of automobile use have always shaped its design, manufacture, and production. ...


Safety-Related Challenges and Opportunities for GPUs in the Automotive Domain

IEEE Micro, 2018

GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as ...


Is Consumer Electronics Redesigning Our Cars?: Challenges of Integrated Technologies for Sensing, Computing, and Storage

IEEE Consumer Electronics Magazine, 2018

This article critically analyzes the trends and limits of integrated technologies for sensing, computing, and data storage when devices and systems originally developed for consumer electronics (CE) are used for self-driving cars. Some hints, supported by theoretical analysis and experimental work, are provided to overcome the issues of inertial sensors, micromirrors for lidar scanners, car data/program memory, and computing platforms.


UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

IEEE Network, 2019

As air pollution is becoming the largest environmental health risk, the monitoring of air quality has drawn much attention in both theoretical studies and practical implementations. In this article, we present a real-time, fine- grained, and power-efficient air quality monitor system based on aerial and ground sensing. The architecture of this system consists of the sensing layer to collect data, ...


More Xplore Articles

Educational Resources on Unmanned Autonomous Vehicles

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IEEE.tv Videos

Navigation and Control of Unmanned Vehicles: A Fuzzy Logic Perspective
Robotics History: Narratives and Networks Oral Histories: Larry Matthies
Self-Driving Cars and Beyond: Societal Impacts of Autonomous Transportation Systems - IEEE TechEthics Panel
A Conversation About Autonomous Transportation Systems: IEEE TechEthics Interview
Robotics History: Narratives and Networks Oral Histories: Chuck Thorpe
Fog Computing's Impact on Autonomous Vehicles: Q&A with Seval Oz at Fog World Congress
IEEE 5G Podcast with the Experts: 5G for large-scale wireless communications between autonomous vehicles
Keynote: Mario Gerla on Internet of Vehicles - WF-IoT 2015
Alberto Broggi accepts the IEEE Medal for Environmental and Safety Technologies - Honors Ceremony 2017
Robotics History: Narratives and Networks Oral Histories: Ernst Dickmanns
The Social and Personal Impacts of AI: IEEE TechEthics Panel
IROS TV 2019- Khalifa University Robotics Institute- Khalifa University of Science & Technology
Enabling Wireless Autonomous Systems with 5G and Beyond
How will 5G drive the self-driving car? Challenges from a V2X solution provider's point of view - Jozsef Kovacs: Brooklyn 5G Summit 2017
Keynote: Planning for Autonomous Systems in the Trentino Region - Paolo Traverso
Beobot 2.0: Autonomous Mobile Robot Localization and Navigation in Outdoor Pedestrian Environment
NEREID: Smart Sensors, Smart Energy & Energy Harvesting - David Holden at INC 2019
IROS TV 2019-U.S. Military Academy, West Point- Robotics Research Center
Keynote: Future Technologies - Bill Chappell at INC 2019
Power: A Fundamental Ingredient of Advanced Science and Applied Technology - Adam Hamilton, APEC 2018

IEEE-USA E-Books

  • Taxis without drivers-or steering wheels

    A COMING MILESTONE in the automobile world is the widespread rollout of Level 4 autonomy, where the car drives itself without supervision. Waymo, the company spun out of Google's self-driving car research, said it would start a commercial Level 4 taxi service by late 2018, although that hadn't happened as of press time. And GM Cruise, in San Francisco, is committed to do the same in 2019, using a Chevrolet Bolt that has neither a steering wheel nor pedals.

  • Expanding the Design Horizon for Self-Driving Vehicles: Distributing Benefits and Burdens

    With over one billion vehicles in the world today, the motorized road vehicle is the pillar of modern society. Since the beginning of the 20th century, the automobile has revolutionized our spaces, practices, cultures, and identities through a complex matrix of technical, financial, economic, political, and social linkages. Visions of automobile use have always shaped its design, manufacture, and production. Now, motorized road transport is set to revolutionize our society once again on a huge scale. Recent technological developments in propulsion, telecommunications, sensing, and in-vehicle computing technology are expanding the range of vehicles? capabilities. A technological convergence is underway, moving towards self-driving vehicle (SDV) technology. These vehicles will utilize computational algorithms, sensors, and communication devices to automatically navigate a variety of environments with limited or no intervention from human drivers.

  • Safety-Related Challenges and Opportunities for GPUs in the Automotive Domain

    GPUs have been shown to cover the computing performance needs of autonomous driving (AD) systems. However, since the GPUs used for AD build on designs for the mainstream market, they may lack fundamental properties for correct operation under automotive's safety regulations. In this paper, we analyze some of the main challenges in hardware and software design to embrace GPUs as the reference computing solution for AD, with the emphasis in ISO 26262 functional safety requirements.

  • Is Consumer Electronics Redesigning Our Cars?: Challenges of Integrated Technologies for Sensing, Computing, and Storage

    This article critically analyzes the trends and limits of integrated technologies for sensing, computing, and data storage when devices and systems originally developed for consumer electronics (CE) are used for self-driving cars. Some hints, supported by theoretical analysis and experimental work, are provided to overcome the issues of inertial sensors, micromirrors for lidar scanners, car data/program memory, and computing platforms.

  • UAV Aided Aerial-Ground IoT for Air Quality Sensing in Smart City: Architecture, Technologies, and Implementation

    As air pollution is becoming the largest environmental health risk, the monitoring of air quality has drawn much attention in both theoretical studies and practical implementations. In this article, we present a real-time, fine- grained, and power-efficient air quality monitor system based on aerial and ground sensing. The architecture of this system consists of the sensing layer to collect data, the transmission layer to enable bidirectional communications, the processing layer to analyze and process the data, and the presentation layer to provide a graphic interface for users. Three major techniques are investigated in our implementation for data processing, deployment strategy, and power control. For data processing, spatial fitting and short-term prediction are performed to eliminate the influences of incomplete measurement and the latency of data uploading. The deployment strategies of ground sensing and aerial sensing are investigated to improve the quality of the collected data. Power control is further considered to balance between power consumption and data accuracy. Our implementation has been deployed in Peking University and Xidian University since February 2018, and has collected almost 100,000 effective values thus far.

  • Advanced Driver-Assistance Systems: A Path Toward Autonomous Vehicles

    Advanced driver-assistance systems (ADASs) have become a salient feature for safety in modern vehicles. They are also a key underlying technology in emerging autonomous vehicles. State-of-the-art ADASs are primarily vision based, but light detection and ranging (lidar), radio detection and ranging (radar), and other advanced-sensing technologies are also becoming popular. In this article, we present a survey of different hardware and software ADAS technologies and their capabilities and limitations. We discuss approaches used for vision-based recognition and sensor fusion in ADAS solutions. We also highlight challenges for the next generation of ADASs.

  • How the Outback Challenge Was Won: The Motivation for the UAV Challenge Outback Rescue, the Competition Mission, and a Summary of the Six Events

    This article describes the motivation for the unmanned aerial vehicle (UAV) Challenge Outback Rescue, the competition mission, and a summary of the six events that have taken place since 2007. In total, more than 350 teams and 2,000 team members competed to see who would be the first to save lost bushwalker, Outback Joe. In 2014, four teams completed the search and rescue mission task and demonstrated that they had developed a cost-effective robot aircraft that could find and save a lost bushwalker in the Australian Outback. We discuss what factors were behind the completion of the competition and we outline some of the significant outcomes that have fed into the UAV industry.

  • A Friendly and Low-Cost Technique for Capturing Non-Cooperative Civilian Unmanned Aerial Vehicles

    As a result of continuous cost reduction and device miniaturization, small UAVs are now more easily accessible to the public. Consequently, numerous new applications in the civilian and commercial domains have emerged. However, despite regulations, non-cooperative UAVs have started to abuse low-altitude airspace with potential security and safety problems. In this work, we present a new GNSS spoofing based counter- UAV defense system, which is able to flexibly, friendly, and remotely control a non-cooperating UAV to fly to a location we specify for capture. Our simulation and field study show the effectiveness of such a defense technique.

  • Introduction to the Special Issue on Precision Agricultural Robotics and Autonomous Farming Technologies

    Growth in world population, increasing urbanization and changing consumption habits mean demand for food production is predicted to increase dramatically over the coming decades. This increased demand for food production must be achieved despite challenges such as climate change, a limited supply of new arable land and difficulties in sourcing skilled farm labour. Robotics and automation are likely to play a crucial role over the coming decades in meeting these challenges by helping to improve farm productivity. A vital component of these future autonomous agricultural systems is the development of robust and accurate perception systems for perceiving the agricultural environment.

  • Robots for In Situ Interventions [From the Guest Editors]

    Conventionally, manufacturers of robotic systems have focused their technological developments on responding to the automation of production lines for new products and/or repetitive tasks. As a result, there is now a large family of industrial robotics with generally similar configurations [serial arrangements of five or six degrees of freedom (DoF)]. However, because these have been developed mainly for open spaces (i.e., large workshops), their capability to access confined environments is rather limited from the points of view of both the workspace and number of DoFs.



Standards related to Unmanned Autonomous Vehicles

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No standards are currently tagged "Unmanned Autonomous Vehicles"


Jobs related to Unmanned Autonomous Vehicles

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