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DEI - FCTUC
Gerado a 2024-03-28 09:58:33 (Europe/Lisbon).
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Titulo Estágio

Vision-based Robot Navigation

Áreas de especialidade

Sistemas Inteligentes

Local do Estágio

Universidade de Coimbra, Polo II

Enquadramento

Mobile robots have been getting more and more autonomous, but some challenges persist. One of the main challenges for a robot that aims to coexist with humans, is the ability to understand its environment and safely navigate through it. Traditionally, the navigation relies on cloud-points from proximity sensors (such as Laser Range Finders). Humans and animals, on the other hand, use vision and their main source of information. For that reason, some work has already been done on using visual information for navigation [1,2]. Moreover, vision also enables the detection and classification of objects and places of interest, which aid in understanding the surroundings [3].
1 - Lategahn, H., Geiger, A., & Kitt, B. (2011, May). Visual SLAM for autonomous ground vehicles. In 2011 IEEE International Conference on Robotics and Automation (pp. 1732-1737). IEEE.
2 - Williams, B., & Reid, I. (2010, May). On combining visual SLAM and visual odometry. In 2010 IEEE International Conference on Robotics and Automation (pp. 3494-3500). IEEE.
3 - Chen, C., Fragonara, L. Z., & Tsourdos, A. (2021). RoIFusion: 3D Object Detection From LiDAR and Vision. IEEE Access, 9, 51710-51721.

Objetivo

The main goal of this dissertation is to design, implement and test a framework that enables a robot to safely navigate an environment and identify places and objects of interest using visual information. The work will investigate the applicability of Evolutionary Machine Learning [4] techniques for producing Convolutional Neural Networks for this task [5].

The various modules of the robot shall be integrated using the Robot Operating System (ROS) framework.

4 - Mirjalili, S., Faris, H., & Aljarah, I. (2019). Evolutionary machine learning techniques. Springer-Verlag GmbH.
5 - Bengio, Y. (2009). Learning deep architectures for AI. Foundations and trends® in Machine Learning, 2(1), 1-127.

Plano de Trabalhos - Semestre 1

Plano 1 semestre
Passo 1 - Literature review.
Passo 2 - First steps with a mobile robot.
Passo 3 - Definition of the techniques and technologies that will be used.
Passo 4 - System Architecture Design
Passo 5 - Implementation of the first version of the system
Passo 6 - Writing of the intermediate report

Plano de Trabalhos - Semestre 2

Plano 2 semestre
Passo 7 - Analysis of the first prototype and the obtained results
Passo 8 - Refinement of the prototype
Passo 9 - Validation in a realistic environment
Passo 10 - Scientific Article with the main results
Passo 11 - Writing of the thesis

Condições

The work will be carried out in the Laboratory of Embedded Systems of the Institute of System and Robotics (next to the Department of Electrical Engineering of the University of Coimbra).
Depending on the quality of the work carried-out, there is a possibility of the student being awarded a scholarship (Bolsa de Investigação para Licenciado) for the last 3 months, renewable by agreement between the advisor and the intern. The scholarship will follow the Fundação para a Ciência e Tecnologia (FCT) monthly stipend guidelines.

Orientador

Lino Marques
lino@isr.uc.pt 📩