Research Project

LOGIMATIC: Tight integration of EGNSS and on-board sensors for port vehicle automation


European Project

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Project Description

Annual volume at global container terminals will rise by a 5.6% rate during the next 5 years and reach 840 million TEU by 2018.The usual way for ports to deal with the increasing demand of sea transport and compete against competitors is to expand the port in the original site. There is scarcity of land available for port expansion in densely populated urban areas where most of European ports are situated. This fact is causing that many container terminals are coping with congestion and capacity problems. Therefore, port managers are searching for more efficient and cost-effective means in the handling of containers while still trying to introduce innovative technical solutions. Container handling equipment automation is an innovative technological solution that contributes not only to improve the utilization rate of equipment and reduce operating costs, but also greatly improve efficiency of terminals.
LOGIMATIC proposes an ad-hoc advanced location and navigation solution to enable the automation of existing port vehicles with a significantly lower cost which will allow short-medium term investments until the whole port fleet is renewed with totally autonomous vehicles in the long term. The project will develop and demonstrate an innovative location and navigation solution for the automation of the operations of straddle carriers in container terminals.
● To develop an advanced automated navigation solution based on the integration of Global Navigation Satellite Systems (GNSS) and sensors onboard the SC vehicles.
● To implement a GIS-based control module compatible with existing Terminal Operating Systems (TOS) for optimized global (yard level) route planning and fleet management.
● To implement security mechanism in order to detect and avoid spoofing and/or jamming attacks
● To assess the impact of application of such automated approach at large scale through simulation
● To integrate, validate and demonstrate the proposed solution in a real port yard.

Project Publications

Journal Publications

  • J. Deray, J. Solà and J. Andrade-Cetto. Word ordering and document adjacency for large loop closure detection in 2D laser maps. IEEE Robotics and Automation Letters, 2(3): 1532-1539, 2017.

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  • M. Villamizar, J. Andrade-Cetto, A. Sanfeliu and F. Moreno-Noguer. Boosted random ferns for object detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017, to appear.

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Conference Publications

  • A. Agudo and F. Moreno-Noguer. DUST: Dual union of spatio-temporal subspaces for monocular multiple object 3D reconstruction, 2017 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2017, Honolulu, USA, IEEE, to appear.

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  • V. Vaquero, I. del Pino, F. Moreno-Noguer, J. Solà, A. Sanfeliu and J. Andrade-Cetto. Deconvolutional networks for point-cloud vehicle detection and tracking in driving scenarios, 8th European Conference on Mobile Robots, 2017, Paris, France, to appear.

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  • A. Agudo and F. Moreno-Noguer. Global model with local interpretation for dynamic shape reconstruction, 2017 IEEE Winter Conference on Applications of Computer Vision, 2017, Santa Rosa (California), USA, pp. 264-272, IEEE.

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