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Mobile Robotics

Work description

Literature Review:

1. Review of previous work on localization using 3D sensors;
2. Analysis of current technologies, identifying their limitations and areas for improvement.

Data Acquisition:

1. Selection of the most suitable 3D sensors (e.g. LiDAR, stereo cameras);
2. Planning data collection in different environments;
3. Identification of relevant public datasets.

Resource Engineering:

1. Feature Extraction: Identification of the most relevant features, such as curvature, normals and distances;
2. Feature Selection: Choose the most important features using techniques such as: o Correlation analysis;
3. Importance of features (feature importance);

Dimensionality reduction.

Algorithm Development and Training:

1. Defining the model architecture, choosing the algorithm and carrying out tests with different configurations and hyperparameters;
2. Training: Division of collected data into training, validation and test sets.

Experimenting with various optimization techniques such as gradient descent and stochastic descent.

Performance Analysis and Refinement:

1. Assessment of model performance on the validation set, using relevant metrics (e.g., precision, accuracy, recall, F1-score);
2. Model Refinement: Adjusting the model by modifying hyperparameters, adding or removing features, or exploring different architectures;
3. Consideration of techniques such as transfer learning or ensemble methods.

Compilation of Results and Final Report:

1. Compilation of results obtained throughout the project;
2. Writing of the final report, detailing the work carried out and the conclusions drawn

Academic Qualifications

Bachelor's degree in engineering or related field;

Minimum profile required

Enrollment in a Master's degree in Electrical and Computer Engineering, Computer Engineering, or related areas;

Preference factors

Experience in Artificial Vision, Artificial Intelligence, ROS;

Maintenance stipend: € 990,98, according to the table of monthly maintenance stipend for FCT grants , paid via bank transfer. Grant holders may be awarded potential supplements, according to a quarterly evaluation process (Articles 19, 21 and 22 of the Regulations for Grants of INESC TEC and Annex II), up to a maximum limit of 50% of the monthly maintenance stipend.

INESC TEC supports costs with registration, enrolment or tuition fees, during the grant duration, under the terms established in the internal document: "Payment of Tuition fees to grant holders".

The grant holder will benefit from health insurance, supported by INESC TEC.

Application Period

Since 26 Sep 2024 to 09 Oct 2024

Centre

Robotics in Industry and Intelligent Systems

Scientific Advisor

Héber Miguel Sobreira

What we offer

• Multicultural and collaborative environment
• A multicultural, international and collaborative environment that makes it easier to exchange ideas, work in networks and create synergies.
• International projects
• The possibility of working in international projects with some of the most important companies in the field.
• Mentoring
• Mentoring with the best researchers in the fields of electrical and industrial engineering, bioengineering, information technology and physics.
• Self Improvement
• The possibility of participating in international conferences, workshops, seminars and vocational training.
• Other Benefits and Perks
• Flexible working time, health insurance, discounts in hotels, transportation, etc.
• Informal Events
• Annual informal events, such as the multicultural party.

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