Grid Coloring for Object Sensing and Localization
Il y a 6 mois
Contexte et atouts du poste
Within the framework of a partnership with Nokia Bell Labs.
Starting time: Position available immediately (duration 6 months).
Mission confiée
Internship Supervisors:
Cedric Adjih, Research ScientistDepartment/Lab: INRIA, TRiBE team, Saclay, France
Contact: Chung Shue (Calvin) Chen, Research Scientist
Department/Lab: Nokia Bell Labs, ML & System team, Paris-Saclay, , Contact: Elie de Panafieu, Research Scientist
Department/Lab: Nokia Bell Labs, Math & Algorithm team, Paris-Saclay, , Contact:
Principales activités
Project Description / Internship Subject
A robot moves on a grid or topology. At each position, it perceives the multiset of sensing of the tiles or surroundings that it covers. The goal of the project is to design and code an algorithm that labels the grid so that the robot can uniquely determine its location due to the combination of the sensed labels.
The fewer the number of bits used to represent all the required labels for the system or network, the better.
For example, in the following grid, no two 3-by-3 square contains the same multiset of the labels (we use color to illustrate, which however can mean an identification number or a few bits).
We would propose interesting new mathematical models which may spur future scientific research. Interesting engineering application includes 6G wireless IoT systems.
Research methodology to be used:
Several approaches of increasing sophistication can be applied. Greedy algorithm, algorithms improving a coloring of graph by solving local conflicts randomly, graph neural networks (as the problem is reminiscent of, but distinct from, graph coloring), machine learning and deep learning techniques.
References
1. C. Adjih, C. S. Chen, C. S. Gobin, and I. Hmedoush, "Designing Medium Access Control Protocol Sequences Through Deep Reinforcement Learning," European Conference on Networks and Communications & 6G Summit, 2023.
2. Y. Shao, S. C. Liew and T. Wang, "AlphaSeq: Sequence Discovery with Deep Reinforcement Learning," IEEE Trans. on Neural Netw. & Learning Systems, 2020.
3. S.-W. Ho and C. S. Chen, "Visible Light Communication Based Positioning Using Color Sensor," IEEE 8th Optoelectronics Global Conference (OGC), 2023.
4. C. S. Chen, Y.-H. Lo, W. S. Wong, and Y. Zhang, "Object Tracking Using Multiset Color Coding," Preprint, 2024.
The te am:
Inria is the French national research institute for digital science and technology. World-class research, technological innovation and entrepreneurial risk are its DNA. In 220 project teams, most of which are shared with major research universities, often
in an interdisciplinary manner and in collaboration with industrial partners to meet ambitious challenges. Saclay research centre is located at the heart of the Paris-Saclay scientific and technological excellence cluster. Serving the development of the Université Paris-Saclay and the Institut Polytechnique de Paris, the Inria Saclay centre has 60 people working in research support services and 600 scientists working in 37 project teams. It offers a unique environment to talented candidates in the field of technological and software development.
Nokia creates the technologies to connect the world. With the research and innovation capabilities of Nokia Bell Labs, we provide network service providers, governments, large business companies and end users with the most comprehensive portfolio of products, services and licenses on the market. Nokia Bell Labs is the world-renowned research arm of Nokia, having invented many of the foundational technologies that underpin information and communications networks and all digital devices and systems. Within Bell Labs, AI Research Lab conducts fundamental and applied research in machine learning, mathematics, modeling, and optimization. The Lab has a long tradition of excellence in research and currently consists of over 80 staff members with expertise in algorithmic and computing sciences, network measurement and optimization, information theory and machine learning.
Compétences
Skills that are useful/that you will acquire:
Combinatorics, number and coding method/theory, graph representation and discrete mathematics, algorithm design, programming and software implementation, machine learning and deep learning method, engineering practice and industrial experience
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.) Possibility of teleworking (after 6 months of employment) and flexible organization of working hours 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
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