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Available Ph.D. positions


If available, call for Ph.D. positions are listed in this page (please check the deadlines for your application). Access to Ph.D.in Italy is subject to a public examination. Please refer to the following PhD program pages for the specific requirements and deadlines. ScuDO – Politecnico di Torino: requirements and call for applications

If you are interested into a proposal and wish to submit your application for the position, send us an email with the following information:


Available Thesis


Enhancing Verbal Communication with Multiple Virtual Agents in Collaborative VR Environments

Thesis @CGVG
Tutors: Edoardo Battegazzorre, Stefano Calzolari, Andrea Bottino
TAGS: Virtual Reality, Multi-Agent Systems, Natural Language Processing, Human-Agent Interaction, Collaborative Interfaces

Virtual reality (VR) environments increasingly rely on the interaction between users and virtual agents, particularly in tasks requiring teamwork and collaboration. However, managing verbal communication with multiple agents presents unique challenges, such as discerning the intended recipient and ensuring accurate interpretation of commands. This thesis aims to address these challenges by investigating and developing systems that facilitate seamless communication with multiple virtual agents in VR settings.

The project will begin with an analysis of current solutions and approaches for multi-agent communication in VR. Based on these findings, a VR application will be developed to implement some of these systems for managing verbal interactions with multiple agents in a shared context. These systems may involve different strategies for agent recognition, dialogue management, and Natural Language Processing (NLP).

The final phase of the thesis will involve conducting user tests to evaluate the implemented systems. These tests will assess key factors such as usability, efficiency, and user satisfaction, providing insights into the strengths and weaknesses of each approach.

Required Skills:

Towards enhanced anomaly segmentation in driving scenarios: developing a multi-modal synthetic dataset with CARLA

Thesis @CGVG in collaboration with VANDAL group
Tutors: Carlo Masone, Leonardo Vizzani, Andrea Bottino
TAGS: Synthetic 3D Multimodal Dataset, Anomaly Detection, Autonomous Vehicles, Anomaly Segmentation, CARLA Simulator, Multi-Modal Sensor Data

The ability to detect anomalies in driving scenes is crucial for the safe deployment of autonomous vehicles. Current benchmarks for anomaly segmentation, such as FishyScapes, SegmentMeIfYouCan (SMIYC), and RoadAnomaly, offer some insights into this challenge. These datasets primarily focus on anomalies as new, unseen objects placed on the road, represented through monocular camera images. However, this narrow definition fails to capture the broader and more complex nature of anomalies. Anomalies can also include familiar objects in abnormal configurations (e.g., a fallen tree or a car in an unusual position), as well as environmental or contextual irregularities. This thesis proposes to address these limitations by creating a new synthetic dataset using the CARLA driving simulator. In particular, we aim to:

Design and Development of Interactive 3D Virtual Reality Environments for Substance Use Disorder Monitoring and Treatment

Thesis @CGVG in collaboration with University of Turin and University of Maryland
Tutors: Andrea Bottino, Elisa Carlino (unito), Lola Akintola-Mala (umaryland)
TAGS: Virtual Reality, Substance Use Disorder, Behavioral Monitoring, 3D Simulation, Interactive Environments

Substance use disorders (SUDs) are a critical global health challenge, affecting millions of individuals and their communities. Addressing the behavioral, psychological, and neurobiological dimensions of substance use requires innovative tools that can simulate real-world scenarios and offer controlled environments for study and intervention. VR technology has emerged as a powerful platform for creating immersive and interactive simulations, offering unique opportunities to explore and address substance use in a safe, replicable, and engaging manner.

This thesis focuses on the design, development, and testing of interactive 3D virtual reality environments to simulate real-world scenarios associated with substance use and misuse. The project will explore the creation of multiple immersive environments tailored to represent diverse settings, including social gatherings, clinical contexts, and educational spaces. These environments will serve as platforms for both research and intervention, enabling the study of substance use behaviors and the testing of innovative treatment strategies.

The proposed work aims to incorporate advanced technologies to enhance the functionality and interactivity of these virtual environments. This includes the integration of tools for recording and coding eye-tracking, motion data, and ecological momentary assessments (EMA), as well as leveraging LLMs to enable context-aware, dynamic interactions.

The main project activities include:

The project will be conducted in collaboration with the Colloca Lab at the University of Maryland, Baltimore, USA, and primarily based at the Polytechnic University of Turin. This partnership offers a unique opportunity for interdisciplinary research, combining expertise in VR technology, behavioral health, and clinical practice. Additionally, there is potential for a visiting period at Colloca Lab.

LLM-Agent with Memory Modules

Thesis @CGVG
Tutors: Alessandro Pecora, Andrea Bottino
TAGS: AI, Memory-Augmented Neural Networks, LLM-Agents, Natural Language Processing, Conversational Agents

This thesis focuses on the integration of memory modules into large language model agents (LLM-Agents) to improve their ability to retain, retrieve, update and in general utilize information across interactions and from external knowledge sources. The primary objective is to design and develop memory architectures specifically tailored for LLM-Agents, enabling intelligent prompt management to integrate memories from past interactions or information from external knowledge seamlessly.

This research involves a comprehensive review of the state of the art, with a particular focus on open-source models to ensure resource efficiency and performance feasibility. Additionally, it aims to develop LLM-Agents optimized for specific applications and domains—such as AI companions, personalized learning platforms, and AI secretaries—while establishing robust evaluation methods to assess the performance of the memory modules and the LLM-Agent as a whole.

Based on the review, the LLM-agent developing will focus on the following tasks:

Using Large Language Models (LLMs) to Generate Complex Branching Stories: Analysis, Design, and Experimentation

Thesis @CGVG in collaboration with University of Turin and Museo Egizio di Torino
Tutors: Andrea Bottino
TAGS: Narrative Theory, Large Language Models, Interactive Storytelling, Branching Narratives, Story Design, Prompt Engineering

Large Language Models (LLMs), such as ChatGPT, represent a promising tool for the creation of interactive narratives, particularly branching stories where user choices lead to different paths and outcomes. This thesis aims to explore the design and implementation of a system capable of generating such stories, scene by scene, while maintaining stylistic and structural coherence throughout the narrative.

The core of the project involves the design of a framework for structuring the skeleton of a branching story. This framework organizes the story into interconnected scenes, where branching points represent choices that split the narrative into different paths. For each scene, the creator defines key elements, such as characters, locations, and objects, alongside a brief description of the intended events, mood, and tone. The system will use these inputs to generate the entire story, ensuring consistency across all scenes while respecting the branching structure.

The primary objective of the thesis is to conduct prompt engineering to enable LLMs to generate scenes that adhere to these specifications. This process will involve crafting and iterating on prompts that effectively guide the model to produce coherent, engaging, and contextually appropriate scenes based on the predefined structure and elements. Achieving this will require integrating insights from established theoretical frameworks for designing branching narratives and studying best practices in the literature on LLM applications for storytelling tasks.

Improving Training and Learning Methods in eXtended Reality

Thesis @CGVG, available for multiple students;
Tutors: Andrea Bottino, Edoardo Battegazzorre, Francesco Strada
TAGS: Mixed Reality, Animation, Training, Education

Training and learning in XR (VR/AR) in several scenarios (industrial, medical, educational) can be envisage as actvities characterized by a sequence of activities that can be organized in procedures. The activity organization can differ according to the specific scenario (e.g., activities can be sequential, alternative, looped and so on), anc can be generally represented as a graph of activities.

The learning phase is then usually organized in different steps (or phases):

As said before, this structure is standard in many application fields. The general objective of this proposal is to facilitate the development of such learning program and improve their effectiveness.

Research methods

An educational path can be structured through different learning methodologies, different assessment systems and activities organization (looped sequences, repeat only mistakes, and so on). However, the effectiveness of these approaches and the best combination of learning/assessment/organization methods is also related to the context where learning/training activities take place.

The objective of this thesis is to make a review of the state of the art to identify the most promising approaches, and to validate their effectiveness in different real-world contexts, in terms not only of knowledge and skill acquisition, but also of their retention over time

Topic 2: software farmework for rapid prototyping of MR-based learning environments

A first thesis topic is developing a software framework that allows a fast deployment of a learning program by defining the structure supporting activities, procedures and their scheduling, so that the designer of the educational intervention is only required to: i) create the assets to be used in the MR environment, ii) define the logic of the single activity, and iii) design the activity graph that define the procedures.

Students are required to implement the framework and develop at least two different use case scenario (in different fields, e.g., medical and industrial) to test it.

Topic 2: usability and UX of the learning environments

A second thesis topic is analyze the problem in terms of usability and User eXperience, i.e. analyze how to better deliver instructional/educational content in immersive AR/VR experiences, how to develop effective HCIs (in terms of input/output) and how to actively support users during their learning program (e.g., by adding AI-driven virtual instructors that can provide a natural and “face-to-face” support for the user).

Students are required to analyze the problem, proposed alternative solutions that can be implemented in the HCI, and validate them trough quantitative/qualitative assessment involving a panel of users. For this task, at least one use case scenario (in any possible field…) must be developed from scratch

Topic 3: development of an effective debriefing support

A third topic is the development a debriefing companion application, which relies on the analytics (and other data) collected during the rehearsal and evaluation sessions. The availability of a debriefing step is extremely relevant for knowledge retention, since it helps learners to reflect on what they did, get insights from their experience and make meaningful connections with the real world, thus enhancing transfer of knowledge and skills. Even when results are not as successful as the learners hoped, debriefing can still promote active learning by helping them to analyze mistakes made and explore alternative solutions.

Students are required to analyze the problem, proposed alternative solutions that can be implemented in the debriefing companion app, and validate them trough quantitative/qualitative assessment involving a panel of users. For this task, at least one use case scenario (in any possible field…) must be developed from scratch.

XR FRAMEWORK FOR COLLABORATIVE LEARNING and collaborative work

Thesis @CGVG, available for multiple students;
Tutors: Andrea Bottino, Francesco Strada
TAGS: Mixed Reality, Animation, Training, Education

The goal of this work is to evaluate and implement solutions that allow simultaneous access to a three-dimensional environment in which two or more users interact with each other and with the environment. Three application scenarios are proposed below:

  1. Use for educational purposes in a classroom where the professor and students access the same application from different devices. A plausible scenario consists of:
  2. Professor using a tablet or PC version of the application to highlight objects/points of interest;
  3. VR device used by one or more students to perform operations on three-dimensional objects within the scene;
  4. Touch device (e.g. lim) that allows interacting with objects in the scene and performing the same operations intended for virtual reality devices, but with different input devices (touch screen);
  5. Use for remote assistance, which allows a technician/student (equipped with smart glasses) who wants to perform work on a machine/a trainign activity to receive real-time assistance from a senior operator/an expert who can connect to the machine via an app (desktop or VR) and view its 3D and related data. The senior can geographically locate the junior using the 3D model or the camera on the smart glasses and tell him where to go to work. It would be interesting to be able to give the junior the feeling of the senior's presence as well.

The objective of the thesis will be to evaluate the effectiveness of the possible solutions through the implementation of different use cases in both medical and industrial scenarios.

Entertainment games for complex problem-solving: implementing game design feature for fostering knowledge and skill acquisition

Thesis @CGVG
Tutors: Andrea Bottino, Carlo Fabricatore, Dimitar Gyaurov
TAGS: Serious Games, Complex Problem Solving, Design guidelines, Game design

Serious games are an innovative alternative to traditional educational methods, capable of promoting modern learning processes through engaging gameplay experiences. However, while entertainment games demonstrate high effectiveness in fostering learning through gameplay, educational games often struggle to achieve the same levels of engagement and transferability of skills to the real world. Specifically, developing cognitive skills for complex problem solving (CPS) is a challenge that many formal learning environments and educational games fail to address adequately.

This thesis aims to explore which design features from entertainment games can be leveraged to create serious games that effectively stimulate CPS and promote effective and transferable learning.

Thesis Work Definition:

The thesis will focus on the development of a serious game based on a set of design features identified through a recent systematic literature review of entertainment games and their potential to promote CPS. The project involves the design and creation of a game prototype that incorporates these features and the subsequent evaluation of its ability to foster learning through gameplay.

The candidate will be responsible for defining the game mechanics, programming, and developing the game using the Unity engine, as well as implementing tools for analyzing interactions and learning outcomes.

Required Skills:

Pick and place VR exergame for motion cost estimation

Thesis @CGVG in collaboration with Rehab Technologies Lab, IIT genova
Tutors: Andrea Bottino, Francesco Strada, Stefano Calzolari
TAGS: Neuro-Robotics, Virtual Reality (VR), Exergame Development, Motion Cost Estimation, Rehabilitation Technology

The Laboratory

Rehab Technologies Lab is an innovation lab jointly created by IIT and INAIL (National Institute for Insurance against Accidents at Work) to develop new high tech rehabilitation solutions of high social impact and market potential. The projects so far include: the CE marked poly-articulated hand prosthesis (Hannes), the upper-limb (Float) and the lower-limb (TWIN) exoskeletons, both developed in compliance with the ISO standards for medical devices. Moreover, the laboratory leads and participates in neuro-rehabilitation projects aimed at studying cognitive and physical workload to help neurological patients in improving the quality of life.

Motivations and general objectives

The proposed activities are within the framework of the “NRTWIN - NeuroRobotic TWINning” project, aimed to design, develop, and test a set of neuro-robotic solutions (sensors, computational models, control systems) for replicate virtually physio-motor activities to study mental and physical effort for different population of subjects: healthy individuals, prosthetic users, people with Multiple Sclerosis (MS).

In general, the analysis and understanding of the pick-and-place task is fundamental in various industrial and rehabilitation settings, involving the movement of objects from one location to another. Improving the performance of this task and the required motion cost can have significant implications for ergonomics, productivity, and physical rehabilitation. Virtual Reality (VR) offers a unique platform for creating immersive and controlled environments to study and enhance motor skills. This thesis aims to contribute to the development of a VR-based pick-and-place exergame and to collect and analyze game data to understand the interaction of the individuals with the virtual environment through motion tracking data related to the execution of the task.

Required skills

The exergame is developed inside Unity engine and C#. The candidate is required to expand the existing game structure inside the engine and create customized scripts for data recording (C#) and analysis (MATLAB or Python).

Working location

The candidate can choose between working and being supervised remotely or working on site at the Rehab Technologies Laboratory, IIT (Morego, Genoa, Italy). The remote option will require some short stays (within a week) in Genoa for data acquisitions or application testing.

Max number of students: 1

Computer Vision algorithms for pose estimation of space objects

Thesis @Astroscale France (Tolouse), internship + reserach grant available
Tutors: Vincenzo Pesce, Andrea Bottino
TAGS: Computer Vision, Machine Learning, Space Industry, Python Programming, Synthetic Data

This thesis focuses on the design and development of computer vision algorithms for pose estimation of space objects, a critical task for enhancing in-orbit services and space sustainability. The project involves creating and validating these algorithms using both synthetic data, generated through tools like Blender, and realistic data collected from a test bench. The research aims to contribute to the advancement of technologies that support safe and efficient space operations, aligning with the mission of Astroscale to promote long-term orbital sustainability.

Main Missions

Essential Skills

Desired Skills

About Astroscale

Founded in 2013, Astroscale is the first private company with a mission to secure long-term spaceflight safety and orbital sustainability for the benefit of future generations. Astroscale develops in-orbit services that improve the characterization and deorbit of space debris or extend the life of old satellites. Headquartered in Japan, Astroscale has offices in the United Kingdom, United States, Israel and France. Astroscale has launched its pioneering technology missions, ELSA-d in 2020 and ADRAS-J in 2024, achieving the world’s first successful approach to a non-cooperative space object. Astroscale France (ASFR) was founded in mid-2023 and has grown to approximately 20 staff. Located in the central quarter of Toulouse, we are developing cutting-edge on-orbit services projects, such as a multi-target inspection mission.

Contact

v.pesce@astroscale.com c.magueur@astroscale.com

Using generative AI to create annotated datasets for wet damage identification

Thesis @CGVG, available for multiple students. Reserach grant available
Tutors: Andrea Bottino, Federico D'Asaro, Alessandro Emmanuel Pecora
TAGS: Generative AI, Annotated Datasets, Instance Segmentation, Wet Damage Identification, Synthetic Data Generation, Machine Learning

This work focuses on the automatic detection of wet damages from images.

A major challenge in this work is the lack of annotated datasets large enough to effectively train instance segmentation algorithms. The core idea of this thesis proposal is to use the capabilities of generative AI (GenAI) to create a synthetic dataset of annotated images.

Using a small set of existing annotated images, the work aims to develop GenAI approaches that can extrapolate and generate a comprehensive dataset that simulates different scenarios and conditions of wet damages. This dataset will then be used to train robust instance segmentation algorithms to improve their accuracy and effectiveness in real-world applications.

The expected outcome of this work is twofold. First, to successfully demonstrate the feasibility of using generative AI to create large, diverse and reliable annotated datasets from a minimal number of real annotated images. Second, to evaluate the performance of instance segmentation algorithms trained on these synthetic datasets.

Developing a Comprehensive Digital Twin for the CARLA Simulator: A Case Study in Turin's Urban Environment

Thesis @CGVG avaliable for multiple students
Tutors: Leonardo Vezzani, Francesco Strada, Andrea Bottino
TAGS:Digital Twin, CARLA Simulator, Urban Environment Replication, Unreal Engine, VR

The aim of this thesis is to create an advanced digital twin of an urban environment, specifically focusing on a neighborhood in Turin, Italy, and integrating it with the CARLA simulator. This project encompasses the development and integration of various components required for a highly effective and realistic driving simulator.

Goals and Objectives:

Urban Environment Replication:

Integration of Autonomous Agents and Realistic Elements:

Real-Time VR Environment Implementation:

Methodology for Continuous Update and Replication:

Use of Advanced Technologies:

Research-Oriented Tool Development:

This thesis represents a blend of simulation technology, urban planning, and software engineering. It offers a unique opportunity for students to contribute to the growing field of digital twins, particularly in the context of urban environments and autonomous driving simulation. The project not only aims to create a realistic digital replica of a neighborhood but also establishes a replicable framework that can be applied to various urban settings, thereby contributing significantly to research and development in this field.

Development of a Modular HUD Design Tool for the CARLA Driving Simulator

Thesis @CGVG avaliable for multiple students
Tutors: Leonardo Vezzani, Francesco Strada, Andrea Bottino
TAGS: HUD Design, CARLA Simulator, Unreal Engine 5, VR

This thesis deals with the development of a tool for the development of sophisticated and modular Head-Up-Displays (HUD) for the CARLA driving simulator. HUDs, which project important information onto a vehicle's windshield, have become increasingly prevalent in modern vehicles and offer the advantage of reducing driver distraction and increasing road safety. This tool aims to replicate and extend the functionality of real HUDs in a virtual driving environment.

Aims and objectives:

Development of a modular HUD tool:

Integration into the CARLA simulator:

Diverse interface and system testing:

Design the user interface and driving experience:

Evaluation through case studies:

Contribution to research:

MASTER THESIS AT EST@ENERGY CENTER

Thesis In collaboration with Energy Center, Politecnico di Torino
Tutors: Andrea Bottino, Francesco Strada, Daniele Grosso, Ettore Bompard
TAGS: Climate and Energy Transition, Large Language Models (LLM), Prompt Engineering, Data Integration, Jupyter Notebooks, Data Visualization, Interactive Environment, City Sustainability, Scenario Planning, Digital Twin, 3D Modeling, Unity, Decision Theatre.
Details of the thesis are below (or here )

PRODUCTION OF A GENERATIVE BOOK ON THE CLIMATE AND ENERGY TRANSITIONS IN THE MEDITERRANEAN AREA APPLYING A LARGE LANGUAGE MODEL (LLM)

The context: EST has produced in the last years five (5) reports on the climate and energy transition in the Mediterranean area, accumulating a large body of knowledge, data and references. The reports gather information on all the energy technologies (from hydrocarbons to renewables), on maritime transport, and on their emissions of greenhouse gases.

The problem: to structure that volume of information in a manner that is ready and fit for all end users, enabling assisted interactions (open and with predefined prompts), and that can grow with the addition of new information. This goal derives from the limitation of traditional books where contents are static and too profuse, and therefore they are on the one hand quickly outdated, and on the other difficult to consult and not prone to rapid answers to the requests of the reader.

The thesis activity to develop a so-called Generative Book (GB) using LLM technologies, applying the platform BLOOM. The new GB will, using as the basic content the already available five reports and related sources, enable users to interact with the contents in different ways (quick summaries, put forward different questions, develop questionnaires based on the text, obtaining usable output against specific requests, etc); will let users contribute to the contents by for instance indicating useful sources of information, indicating shortcomings, commenting, etc.; and will act as an evolving platform to facilitate the growth and evolution of the contents.

CUSTOM TRAINING AND PROMPT ENGINEERING OF A LLM PLATFORM ON THE ENERGY AND CLIMATE TRANSITIONS IN THE MEDITERRANEAN AREA

The context: EST has produced in the last years five (5) reports on the climate and energy transition in the Mediterranean area, accumulating a large body of knowledge, data and references. The reports make reference to a vast set of documents and data. EST intends to upload all those elements in an LLM-based Generative Book (GB).

The problem: to accelerate the adaptation of an out-of-the-box LLM (BLOOM) for its use with knowledge and contents referring to the Mediterranean energy and climate area.

The thesis activity: to compose and format prompts to maximize the model’s performance regarding the tasks defined for the GB, and to custom train the GB model with datasets taken from the EST reports. This will involve fine-tuning the training parameters, setting up the training environment, and fine-tuning the GB model.

INTEGRATION OF JUPYTER NOTEBOOKS WITH A LLM PLATFORM ON THE ENERGY AND CLIMATE TRANSITIONS IN THE MEDITERRANEAN AREA

The context: EST has produced in the last years five (5) reports on the climate and energy transition in the Mediterranean area, accumulating a large body of knowledge, data and references. Many values are supported by equations and formulae, which are not made explicit in the reports.

The problem: to produce an interactive environment composed of computational documents using the data, equations and explanations present in the EST reports on the energy and climate in the Mediterranean ready for their customised use, visualization and analysis, and integrated into a Generative Book (GB).

The thesis activity: to produce Jupyter notebooks concerning energy and climate in the Mediterranean area to be integrated in an LLM-based GB, connecting software codes, data analytics and text, to work interactively and being customizable by the end users.

DEVELOPMENT OF A DIGITAL PLATFORM FOR SUPPORTING TABLE-TOP EXERCISES APPLIED TO THE CLIMATE AND ENERGY TRANSITIONS IN CITIES

The context: EST supports cities in the elaboration of: i) their transition towards climate neutrality and the related production of Climate City Contracts, and ii) plans for their sustainability. For these goals, EST is developing two digital platforms, CLICC and CITTA, composed of interactive tools for dealing with data and text in a multimedia environment, and a full set of scientific instruments for the calculation and analysis of data. The study of future scenarios for climate neutrality and sustainability demands the interaction with all stakeholders, and the joint study of best alternatives concerning all potential contingencies. These interactions can be structured in the form of Table Top Exercises (TTXs).

The problem: to facilitate the arrangements and implementation of TTXs for cities by means of digital applications in an interactive environment, with the management of narrative scripts, a diversity of timing scales, alternative paths in the presence of contingencies, etc., while recording the decision and actions of all participants. TTxs are role-playing activities in which players respond to scenarios presented by the facilitators.

The thesis activity: to produce an interactive digital platform using open-source technologies for supporting the preparation and the running of TTXs applied to the climate neutrality and sustainability of cities, taking advantage of the existing platforms CLICC and CITTA. The platform should provide facilities for ex-ante preparation of the TTX, for the work of the participants (i.e. players, observers, facilitators, note takers), and for the ex-post analysis and reporting.

DESIGN OF AN INTERACTIVE INTERFACE FOR THE DIGITAL TWIN OF CITIES FOR THE STUDY OF CLIMATE NEUTRALITY AND SUSTAINABILITY

The context: EST supports the city of Torino in their plans to climate neutrality and sustainability. A crucial aspect of this support is to enable the city administrators and all city stakeholders to visualize and interact with a digital twin of the various main components of the city (e.g. energy, transport, waste, green areas, etc.) directly related to the production and mitigation of emissions. EST is developing two digital platforms, CLICC and CITTA, composed of interactive tools for dealing with data and text in a multimedia environment, and a full set of scientific instruments for the calculation and analysis of data. EST operates a Decision Theatre with a 180 degrees, 3 meter tall wall where to display interactive software applications.

The problem: to facilitate the interaction with the manifold aspects related to climate neutrality and sustainability of cities, including the virtual representation of the city systems as a digital twin. This representation should include both past data and future scenarios, with the possibility of displaying the evolution in time of those scenarios.

The thesis activity: to produce an interactive interface based on open-source tools such as Unity, to be used in both EST’s Decision Theatre and the web, able to dynamically exhibit data in 2D/3D, and create game-like experiences based on the climate neutrality and sustainability scenarios produced by CLICC and CITTA. The activity will be applied to the city of Torino.

Development of sampling pattern for first degree aberration in raytracing rendering

Thesis @CGVG, available for multiple students.
Tutors: Leonardo Vezzani, Francesco Strada, Andrea Bottino, Bartolomeo Montrucchio
TAGS: Ray Tracing, Rendering, Sampling pattern, Point Spread Function, optical transfer function

The quality of renderings using ray tracing has become increasingly higher, thanks to recent advancements in computer graphics. Despite these advancements, some significant optical defects that characterize photographs taken with real lenses have yet to be implemented in various rendering engines.

This thesis aims to implement the optical defects of a physical lens in a virtual renderer. Specifically, the aim is to introduce first-order optical defects by manipulating the sampling pattern of the renderer to achieve a realistic appearance in both out-of-focus and in-focus planes of the rendered image.

This thesis seeks to re-implement the technology in the open-source renderer Mitsuba (https://www.mitsuba-renderer.org/), starting from a previous algorithm implementation in Blender. The resulting algorithm will be tested using objective and subjective measures to assess the quality of its renders.

Enhancing locomotion in Virtual Reality: The Development and Analysis of Walking Seat V2

Thesis @CGVG
Tutors: Leonardo Vezzani, Francesco Strada
TAGS: VR, locomotion methapores, leaning interfaces, input devices

Walking Seat V2 represents an advanced solution for locomotion in virtual reality (VR), utilizing seat pressure sensors for more intuitive and responsive movement.

Despite various approaches to VR locomotion discussed in literature (Locomotion Vault), the challenge remains largely unresolved. Our innovative device, the Walking Seat, is designed to improve VR navigation significantly. This thesis is dedicated to advancing this technology, focusing on critical aspects such as enhancing sensor density and refining data interpretation. A key challenge to address is distinguishing between leaning movements for navigation and object interaction within the VR space.

This research goes beyond mere development; it involves rigorous testing of the Walking Seat, alongside a comparative analysis with existing locomotion methods. Key objectives of this study include:

Additionally, this study encourages the exploration of various implementation alternatives and innovative approaches to further refine VR locomotion.

Animating Virtual Characters in Unity Using Generative AI: A Prompt-Based Approach

Thesis @CGVG, available for multiple students
Tutors: Stefano Calzolari, Andrea Bottino, Francesco Strada
TAGS: diffudion models, prompt-based generative AI, NPC animation, VR, Unity

This Master's thesis delves into the innovative intersection of generative artificial intelligence and virtual character animation within the Unity environment. The primary focus is on exploring and utilizing diffusion models for prompt-based animation generation, a cutting-edge approach in the realm of AI-driven content creation.

Key Tasks:

  1. Literature Review on Diffusion Models for Prompt-Based Animation Generation: The student will conduct a comprehensive review of existing literature. This involves studying the current state and advancements in diffusion models, specifically how they are applied to generate animations based on textual prompts. This review will help in understanding the theoretical foundation and practical applications of these models in the context of animation.

  2. Implementation of a Generative AI Solution for Unity Character Animation: The practical aspect of this thesis involves implementing a solution, potentially building upon existing models. The objective is to develop a system capable of animating a standard character in Unity based on prompts. This will require integration of AI models with the Unity engine, ensuring that the system is not only functional but also efficient and user-friendly.

Expected Outcomes:

This thesis is an opportunity to contribute to the emerging field of AI in game development and animation, offering practical experience in implementing advanced AI techniques in a popular game development platform.

MPAI-MMM: MPAI Metaverse Model Arhitecture

Thesis @CGVG in collaboration with MPAI consortium, available for multiple students
Tutors: Andrea Bottino, Francesco Strada
TAGS: metaverse, distributed VR, MPAI-MMM, virtual classroom

Metaverse is the name given to a collection of application contexts in which humans, represented by avatars, engage in educational, social, work-related, recreational activities, etc. MPAI (Moving Picture, Audio, and Data Coding by Artificial Intelligence), of which PoliTo is a founding member, has developed a standard for a portable avatar format (Portable Avatar Format) and a standard for metaverse architecture (MPAI Metaverse Model – Architecture). PoliTo is creating the reference code for the use case Avatar-Based Videoconference, where humans participate in a virtual conference with their portable avatars. The use case is implemented as a stand-alone solution.

The proposed thesis, however, concerns the study of an innovative teaching method carried out in the context of the MPAI Metaverse Model – Architecture in which students and the teacher attend the lesson through their portable avatars, exploiting the functionalities of the metaverse.

Details about the MPAI Metaverse standard can be found here.

The Use of Interactive Virtual Scenarios in Personnel Training and Product Presentation: An Analysis of Graphic Optimization for Different Devices

Industrial thesis @ SynArea
Academic tutor: Andrea Bottino, Francesco Strada
TAGS: VR, Training, Product presentation

Technological advancements have made it possible to use interactive virtual scenarios to simulate reality using advanced rendering and graphic techniques. These scenarios can be used in various contexts, such as product presentation and personnel training in the management of industrial machinery. However, graphic optimization for different devices is crucial to ensure a smooth and high-quality experience.

The objective of this thesis is to analyze the use of interactive virtual scenarios in personnel training and product presentation, with particular attention to graphic optimization for different devices. The expected results includes highlighting the advantages and analyzing the challenges associated with the current proposal. The results obtained can be used by companies to improve user experience and ensure a good quality of interactive virtual scenarios.

Required skills Basic skills in the field of 3D graphics, software development and game engine programming.

The activities will take place in Turin:

SynArea Consultants C.so Tortona 17

Polythecnic of Turin (when possible)

CGVG Thesis