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The FLeet of Autonomous Robots and Fleet Management Software

Advoard Robotics produces fully autonomous mobile robots that are aware of each other's location and route information, and develops software to prevent inefficient picking and labor losses in logistics and e-commerce warehouses.... ver más

30/06/2024

ADVOARD ROBOTIK AR...

75K€

Presupuesto del proyecto: 75K€

Líder del proyecto

ADVOARD ROBOTIK ARGE YAZILIM VE SANAYI ANONIM... No se ha especificado una descripción o un objeto social para esta compañía.

Financiación concedida El organismo HORIZON EUROPE notifico la concesión del proyecto el día 2024-06-30

HORIZON-EIE-2022-SCALEUP-02-02: Women TechEU ExpectedOutcome:Project results are expected to contribute to the following expected outcomes:

Innovación

Cerrada hace 2 años

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1 Participantes

ADVOARD ROBOTIK ARGE YAZILIM...

75.00K€ | Lider

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Duración del proyecto: 12 meses Fecha Inicio: 2023-06-02
Fecha Fin: 2024-06-30

Líder del proyecto

ADVOARD ROBOTIK ARGE YAZILIM VE SANAYI ANONIM... No se ha especificado una descripción o un objeto social para esta compañía.

Presupuesto del proyecto 75K€

Descripción del proyecto Advoard Robotics produces fully autonomous mobile robots that are aware of each other's location and route information, and develops software to prevent inefficient picking and labor losses in logistics and e-commerce warehouses. These robots can be monitored through an advanced web interface; remote accident support and data analysis can be done. At the same time, data can be exchanged with the warehouse management system. This solution includes mapping, positioning, path planning, autonomous driving capability of each robot and sharing this information. Robots moving in fleets work with maximum efficiency at minimum route length thanks to algorithms based on artificial intelligence. The technology we have developed includes mapping, positioning, path planning, autonomous driving capability of each robot and sharing this information. Robots that move in fleets work with maximum efficiency at minimum route length thanks to algorithms based on artificial intelligence. The most important technologies used are SLAM (simultaneous positioning and mapping) and FMS (fleet management system). The SLAM process uses a complex set of calculations, algorithms, and sensor inputs to navigate a previously unknown environment or to revise the map of a previously known environment and find a location. Fleet Management System (FMS) is applied to manage and control more than one robot working within the units. FMS provides complete, centralized and decentralized management of the robot fleet, allowing users to manage different mobile robotic systems from a variety of devices via standard communication protocols. In FMS, robots share route and location information with each other. In the light of this information, our algorithms determine the routes in which the robots will perform their tasks without colliding, according to our traffic rule sets.

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