Available Master Thesis
The available master theses are listed below.
Social Robotics Research
A - Realization of a robotic neck to embed social capabilities in a robotic platform
Objective: Realization of a Robot Neck with 3-4 DOF to allow expressive movement to a robotic platform. This component will be social and will move following some movement pattern that conveys an emotional load. The starting point is the revision of a CAD model and the development of the electronics and the 3D printing to physically realize the robot neck. Then, there will be the necessity to embed face detection. The robot will be tested in real environments and some real interactions with people will be implemented. The testing will be done in the University areas with real people who will validate the feasibility and validity of this approach.
Main activities: CAD modeling, electronic prototyping, coding, face recognition, social movement theory
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Laura Fiorini laura.fiorini@unifi.it
B - Design and development of a robot speech system in crowded environments
Objective: Natural language is very important for social robots. The purpose of this thesis is to develop a module for speech interaction based on commercial API and embeddable in our robots. The tasks involve an exploration of various tools and integration in a ROS system, and a work on a hardware module to sample the sound and acquire voice signals effectively in crowded environments.
Main activities: Sound engineering, signal processing, NLP, hardware microphone management
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Laura Fiorini laura.fiorini@unifi.it
C - V-SLAM navigation using 3D camera in complex environments and obstacle management
Objective: Using mobile robots equipped with RGBD cameras, will be possible to work in Computer Vision for Robotics. The work will use ML techniques and image processing to elaborate data and results. The CV algorithms will be finalized to:
- Access Ramp and Stairs detection (for mobile robots/wheelchair)
- Automatic navigation in complex environments (warehouse, hospital)
- Detection of environment features and navigation strategies (e.g. disinfection of flat surfaces)
Main activities: Image processing, Computer Vision, ML, camera specs
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Laura Fiorini laura.fiorini@unifi.it
D - Neuropsychological tests in HRI for social interaction and assessment of executive functions
Objective: The purpose of this thesis is to use a robot manipulator to implement neuropsychological tests and perform them in cooperation with a human. The robot will move differently, depending on the emotion that it wants to stimulate and we will verify how people's behavior changes according to different movements. Another objective will be to perform the same tests with the robot and the human competing for winning and verify what changes in the execution when the robot performs different social movements. Some tests identified for this work are the Iowa Gamblin test, the Brixton Spatial test, and London Tower.
Main activities: Video Processing, AI, Neuropsychological tests, ROS
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Laura Fiorini laura.fiorini@unifi.it
E - Validation of a multimodal system for gait assessment and development of a velocity-based adaptive follow-me system
Objective: Gait analysis using inertial sensors and laser and image data from robots for applications in neurodegenerative diseases. In detail, the activity will include the validation of the laser data with the data recorded by the inertial sensors, as well as the comparison with state-of-the-art devices commonly used for gait rehabilitation.
Main activity: signal processing, sensors integration, experimental protocol, data analysis
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Laura Fiorini laura.fiorini@unifi.it
F - Robots and Augmented Reality as rehabilitation tools
Objective: Rehabilitation therapy with remote control of manipulators or mobile robotic platforms through wearable sensors and Oculus VR. In detail, the Oculus VR will be used as immersive technology to engage the user in the rehabilitation, while the wearable sensors will be used to track the movement performed by the patient and to control the robotic platform.
Main activities: game development, signal processing, sensors integration, experimental protocol, data analysis
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Laura Fiorini laura.fiorini@unifi.it
G - Social Aware Navigation in multiple contexts
Objective: Social aware Navigation with camera and laser data, in single and multiple user contexts (i.e. group arrangement detection), including social norms based on the settings (i.e. hallway or meeting rooms). The objective of this work is to improve the navigation capabilities of a mobile robot in working and clinical settings.
Main activities: feature extraction, navigation stack programming, experimental protocol, data analysis
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Alessandra Sorrentino alessandra.sorrentino@unifi.it
H - Robot as a personalized storyteller
Objective: Personalize the robot profile in terms of emotions and engagement during a storyteller task. The personalization phase will take into account not only the plot of the story but also the user involvement in the listening phase. The personalization will focus on the automatic adaptation of the robot's behavioral cues.
Main activities: literature review, feature extraction, deep learning integration, robot behaviors’ definition and development, experimental protocol and data analysis
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Alessandra Sorrentino alessandra.sorrentino@unifi.it
I - Social Assistive Robots for cognitive assessment and wellbeing
Objective: Design and development of the most appropriate strategies (perception and acting) for a robotic platform for conducting standardized psychological tests. The implemented system will be tested with users for assessing the reliability of the solution as well as the impact and user’s perception with respect to standard paper-pencil administration
Main activities: literature review, feature extraction, deep learning integration, behavioral planning, experimental protocol, and data analysis
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Alessandra Sorrentino alessandra.sorrentino@unifi.it
Wearable Sensors Research
A - Motion Analysis Algorithms for Biomedical Applications
Objective: Development of algorithms for motion analysis in Motor and Cognitive Dual-Task protocols for clinical classification purpose on neurodegenerative diseases
Main activities: Segmentation and analysis of ALTERNATE FINGER TAPPING, TUG and FIGURE of 8 in MCDT protocol for clinical classification purpose.
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi / NeuroCare onlus
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Erika Rovini erika.rovini@unifi.it
B - Sensors Fusion Application on Neurodegenerative Diseases
Objective: Development of an algorithm for clinical classification based on physiological and inertial signals for clinical classification purposes of neurodegenerative diseases
Main activities: Adopt a sensor fusion approach to include physiological signals to study the motor and premotor cortices activation and their relation with the cardiovascular system, to gather information on the motor planning while the subject is performing MCDTs.
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi / NeuroCare onlus
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Erika Rovini erika.rovini@unifi.it
C - Features Design for Biomedical Applications in Neurodegenerative Diseases
Objective: Development of innovative and clinically meaningful kinematic features, starting from a Neuroscientific Framework to better understand the Motor-Cognitive Interface.
Main activities: Identify and implement new features related to motor control, motor harmony/smoothness, motor efficiency, and coordination.
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi / NeuroCare onlus
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Erika Rovini erika.rovini@unifi.it
D - Development of Machine/Deep Learning algorithms for clinical purposes
Objective: Development of innovative and clinically meaningful kinematic features, starting from a Neuroscientific Framework to better understand the Motor-Cognitive Interface.
Main activities: Feature extraction, machine learning, and statistical analysis, experimentation
Duration: 6/8 Months (1 extra month is added for each pending exam during the traineeship period)
Place: Centro didattico Morgagni / Fondazione Don Gnocchi / NeuroCare onlus
Contacts: Prof. Filippo Cavallo filippo.cavallo@unifi.it
Dr. Erika Rovini erika.rovini@unifi.it
Last update
26.09.2023