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Spatial-temporal information processing for collision detection in dynamic environments

Objective

In the real world, collision happens at every second - often results in serious accidents and fatalities. For example, there are more than 3560 people died from vehicle collision per day worldwide. On the other sector, autonomous unmanned aerial vehicles (UAVs) have demonstrated great potential in serving human society such as delivering goods to households and precision farming, but are restricted due to lacking of collision detection capability. The current approaches for collision detection such as radar, laser based Ladar and GPS are far from acceptable in terms of reliability, energy consumption and size. A new type of low cost, low energy consumption and miniaturized collision detection sensors are badly needed to not only save millions of people’s lives but also make autonomous UAVs and robots safe to serve human society. STEP2DYNA consortium proposes an innovative bio-inspired solution for collision detection in dynamic environments. It takes the advantages of low cost spatial-temporal and parallel computing capacity of visual neural systems and realized it in chip specifically for collision detection in dynamic environments.

Realizing visual neural systems in chips demands multidisciplinary expertise in biological system modelling, computer vision, chip design and robotics. This breadth of expertise is not readily possessed within one institution. Secondly, the market potential of the collision detection system could not be well exploited, unless by a dedicated partner from industry. Therefore, this consortium is designed to bring neurobiologists, neural system modelers, chip designers, robotics researchers and engineers from Europe and East of Asia together and complement each others’ research strengths via staff secondments, jointly organised workshops and conferences. Through this project, the partners will build up strong expertise in this exciting multidisciplinary area and the European SME will position well as a market leader in collision detection.
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Coordinator

UNIVERSITY OF LINCOLN

Address

Brayford Pool
Ln6 7ts Lincoln

United Kingdom

Activity type

Higher or Secondary Education Establishments

EU Contribution

€ 517 500

Participants (3)

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UNIVERSITAET HAMBURG

Germany

EU Contribution

€ 121 500

UNIVERSITY OF NEWCASTLE UPON TYNE

United Kingdom

EU Contribution

€ 243 000

AGILE ROBOTS AG

Germany

EU Contribution

€ 126 000

Partners (6)

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TSINGHUA UNIVERSITY

China

NATIONAL UNIVERSITY CORPORATION KYUSHU UNIVERSITY

Japan

XI'AN JIAOTONG UNIVERSITY

China

HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY

China

UNIVERSIDAD DE BUENOS AIRES

Argentina

Guangzhou University

China

Project information

Grant agreement ID: 691154

Status

Ongoing project

  • Start date

    1 July 2016

  • End date

    30 June 2020

Funded under:

H2020-EU.1.3.3.

  • Overall budget:

    € 1 228 500

  • EU contribution

    € 1 008 000

Coordinated by:

UNIVERSITY OF LINCOLN

United Kingdom