Internship : Indoor Visual Positioning

Le descriptif de l’offre ci-dessous est en Anglais_

**Type de contrat **:Stage**Niveau de diplôme exigé **:Bac + 3 ou équivalent**Fonction **:Stagiaire de la rechercheA propos du centre ou de la direction fonctionnelle

The Centre Inria de l’Université de Grenoble groups together almost 600 people in 22 research teams and 7 research support departments.

Staff is present on three campuses in Grenoble, in close collaboration with other research and higher education institutions (Université Grenoble Alpes, CNRS, CEA, INRAE,), but also with key economic players in the area.

The Centre Inria de l’Université Grenoble Alpe is active in the fields of high-performance computing, verification and embedded systems, modeling of the environment at multiple levels, and data science and artificial intelligence. The center is a top-level scientific institute with an extensive network of international collaborations in Europe and the rest of the world.

Contexte et atouts du poste

Mission confiée

We are seeking a highly motivated and talented intern to join Inria’s Experimentation and Development Service (SED). This internship will focus exclusively on the localisation and positioning aspect of autonomous vehicle technology, specifically for navigating vehicles from a parking entrance to a designated parking place within a mapped indoor environment. While the vehicle navigation system is not within the scope of this internship, your work will be crucial in ensuring the vehicle's precise location within this complex indoor environment.

To achieve this goal, you will: (1) study the state of the art in indoor navigation and mapping (visual SLAM, landmark detection, camera pose estimation, optimisation), and (2) test a selected set of algorithms in a simulated environment.

Principales activités
- Collaborate with the SED and the Chroma research engineers to develop and enhance computer-vision based algorithms for precise vehicle localisation within a pre-mapped indoor environment.
- Work on real-time data processing and sensor fusion techniques to optimize positioning accuracy.
- Implement and fine-tune computer vision and machine learning models for robust vehicle positioning, even in cluttered environments with other vehicles and obstacles.
- Conduct experiments and tests in a simulated environment to validate the accuracy and reliability of the positioning system.
- Analyze and interpret data to identify areas for improvement and propose innovative solutions.

Compétences
- Currently pursuing a M1or master's (M2) degree in computer science, electrical engineering, robotics, or a related field.
- Good programming skills in Python, C++ or similar
- Familiarity with computer vision, machine learning, and sensor fusion concepts.
- Solid understanding of mathematics, especially linear algebra and statistics.
- Strong problem-solving skills and the ability to work both independently and in a collaborative team environment.
- Excellent communication and presentation skills.

Avantages
- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage

Rémunération

Gratification = 4,05€ gross / hour