• De Groene Loper 19, Flux

    5612 AP Eindhoven

    Nederland

  • P.O. Box 513, Department of Electrical Engineering

    5600 MB Eindhoven

    Nederland

Organisatieprofiel

Introductie / missie

The Mobile Perception Systems Lab researches methods in Artificial Intelligence that allow mobile autonomous systems to perceive their environment. Our long-term goal is to realize AI that can anticipate on future events in highly dynamic and complex environments. We always validate our AI methods 'in the loop', meaning in the context of challenging real-world applications, mainly from the industry domains of automotive, transportation, and logistics.

MPS is part of the Signal Processing Systems group and we work closely with the Embedded Systems group, the Dynamics and Control group, the Control Systems Technology group, and the TU/e-wide Strategic Area for Smart Mobility.

Highlighted phrase

Perception Through Anticipation

Over de organisatie

The MPS lab specializes in the following AI methods: deep learning, multi-modal computer vision, and simultaneous localization and mapping. These are key enabling technologies that allow mobile sensor platforms to perceive and interpret their environments from past and current sensory data, in essence estimating a dynamic digital world-model in real-time. In coming years, we aim to make a step in the direction of spatio-temporal reasoning engines that allow mobile sensor platforms to predict possible future events and thereby achieve anticipation capabilities. Currently, the lack of anticipation capabilities, is a key bottleneck in deploying mobile autonomous systems in complex and dynamic environments, such as self-driving cars in crowded inner cities. We firmly believe that in order to advance AI and its applications, both an inter-disciplinary approach and a strong cooperation with industry are required. Hence, we are involved in many cross-disciplinary European projects and initiatives, such as the International Connected and Automated Driving Institute (https://icadi.net), and we recently started the company AI In Motion to bring our technologies to the market (https://aiim.ai). 

Vingerafdruk Duik in de onderzoeksthema's waar Mobile Perception Systems Lab actief is. Deze onderwerplabels komen voort uit het werk van deze leden van de organisatie. Samen vormen ze een unieke vingerafdruk.

Semantics Engineering en materiaalwetenschappen
Pixels Engineering en materiaalwetenschappen
Intelligent vehicle highway systems Engineering en materiaalwetenschappen
Labels Engineering en materiaalwetenschappen
Color Engineering en materiaalwetenschappen
Segmentation Rekenkunde
Cameras Engineering en materiaalwetenschappen
Pixel Rekenkunde

Netwerk Recente externe samenwerking op landenniveau. Duik in de details door op de stippen te klikken.

Projecten 2016 2021

Onderzoeksoutput 2014 2020

Fast panoptic segmentation network

de Geus, D., Meletis, P. & Dubbelman, G., 28 jan 2020, In : IEEE Robotics and Automation Letters. 5, 2, blz. 1742-1749

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Segmentation
Pixels
Volatile organic compounds
Pascal
Merging

Semantic foreground inpainting from weak supervision

Lu, C. & Dubbelman, G., apr 2020, In : IEEE Robotics and Automation Letters. 5, 2, blz. 1334-1341 8 blz., 8963753.

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Inpainting
Semantics
Margin
Pooling
Mobile Robot

ABC analysis of an aerospace business case on ALM echnologies in aerospace and defence supply chain

Kemsaram, N., Maley, K. K. & Mahadevan, R., 29 apr 2019, In : Small Enterprises Development, Management & Extension Journal. 46, 1, blz. 24-34 11 blz.

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelProfessioneel

Supply chains
Costs
Industry
3D printers

Prijzen

Best Paper Award

Willem P. Sanberg (Ontvanger), 17 jan 2019

Prijs: AndersWerk, activiteit of publicatie gerelateerde prijzen (lifetime, best paper, poster etc.)Wetenschappelijk

Pers/media

GCDC 2016

Jos den Ouden

31/05/16

1 Mediabijdrage

Pers / media: PR activiteiten

Scripties/masterproeven

Design of a track detection algorithm for a driverless formula student racing car

Auteur: van der Smagt, T., 23 apr 2019

Begeleider: van de Molengraft, R. (Afstudeerdocent 1), Dubbelman, G. (Afstudeerdocent 2) & Barosan, I. (Afstudeerdocent 2)

Scriptie/masterproef: Master

Lane detection and tracking for self-driving vehicles

Auteur: Szutenberg, M., 30 sep 2019

Begeleider: Das, A. (Afstudeerdocent 1) & Dubbelman, G. (Afstudeerdocent 2)

Scriptie/masterproef: Master

Bestand