Grid Coloring Algorithm for Object Localization and Sensing
il y a 3 semaines
Project Overview
As a research intern at INRIA, you will work on designing and implementing an algorithm for labeling a grid to enable a robot to determine its location based on the sensed labels. The goal is to minimize the number of bits required to represent the labels.
Key Responsibilities
- Design and implement a graph coloring algorithm to label the grid
- Develop a system to represent the sensed labels and determine the robot's location
- Explore various approaches, including greedy algorithms, graph neural networks, and machine learning techniques
Collaboration and Support
You will be part of a team of researchers at INRIA and Nokia Bell Labs, working closely with Cedric Adjih, Chung Shue (Calvin) Chen, and Elie de Panafieu. You will have access to professional equipment, training, and social events.
Requirements and Benefits
- Combinatorics, number theory, and graph representation skills
- Experience with algorithm design and programming
- Knowledge of machine learning and deep learning methods
- Subsidized meals, partial reimbursement of public transport costs, and flexible working hours
Research Methodology
Several approaches can be applied, including greedy algorithms, graph neural networks, and machine learning techniques. You will have the opportunity to explore and develop new mathematical models and engineering applications.
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