Human Intention Understanding During Human-human

1 week ago


Sherbrooke, Canada Université de Sherbrooke Full time

**Human Intention Understanding during Human-Human and Human-Collaborative Robot Tasks**:

- Réf
- **ABG-115902**
- Sujet de Thèse- 18/07/2023- Financement public/privé- Université de Sherbrooke- Lieu de travail- Sherbrooke - Canada- Intitulé du sujet- Human Intention Understanding during Human-Human and Human-Collaborative Robot Tasks- Champs scientifiques- Psychologie, neurosciences
- Robotique
- Mots clés- motor control, EEG, EMG, robotics, machine learning**Description du sujet**:

- The primary objective of this Ph.D. project is to investigate and interpret human intentions in the context of cooperative tasks involving both humans and robots. The project will involve conducting a series of natural human-human cooperative tasks and analogous experiments incorporating human-robot collaborations. The study aims to establish a taxonomy of cooperative tasks performed by humans and robots, identifying similarities and differences between the two types of tasks. Data from various sources, including motion capture technology and neurophysiological measurements such as EEG and EMG, will be combined, analyzed, and observed to derive insights.- The project's second contribution involves developing a model of human intention understanding. It is hypothesized that the human nervous system comprehends others' intentions through motor simulation, where observed actions are mapped to the observer's own motor representations. This hypothesis draws support from the discovery of mirror neurons in the monkey premotor cortex, which exhibit similar firing patterns when performing or observing specific actions. The study will explore the relationship between EEG oscillatory activity in the mu rhythm (8-15 Hz), mirror neuron function, and action understanding. By contrasting sensorimotor mu rhythm in scenarios where participants observe either a human or a robot performing an action, and where the intended goal of the action is simple or complex, the project aims to identify differential modulations in mu activity.- To address the challenge of processing the large volume of neurophysiological and biological data (EEG and EMG), the project will leverage machine learning techniques. Recent advancements in machine learning, including classifiers, deep learning, and generative adversarial networks (GANs), will be utilized to classify and process the collected data.**Nature du financement**:

- Financement public/privé**Précisions sur le financement**:

- Financement disponible**Présentation établissement et labo d'accueil**:

- Université de Sherbrooke- Conducting a comprehensive review of the state-of-the-art in neurophysiological signal processing, mirror neurons, and EEG oscillatory activity in the mu rhythm.
- Setting up and conducting experiments to observe and measure neurophysiological signals and kinematics from human participants engaged in cooperative tasks, as well as from a human collaborating with an industrial robot.
- Processing and analyzing the collected neurophysiological and biological signals to establish a taxonomy of cooperative human-human and human-robot tasks. This task also involves implementing machine learning algorithms to handle the large dataset.
- Investigating the underlying human motor control mechanisms involved in task synchronization and execution during collaborative tasks. This task aims to develop a model of human intention understanding, utilizing deep learning algorithms such as Neural Networks, Variational Autoencoders, and Generative Adversarial Networks.- Located in the province of Quebec, Canada, the Université de Sherbrooke is host to more than 31,000 full-time and part-time undergraduate and graduate students. The Université de Sherbrooke stands out for its practical learning methods, promising themes that drive its research units, a strong strategy of innovation, partnership and entrepreneurship, green campuses and an incomparable quality of life between rivers and mountains. All these reasons make it one of the most appreciated universities in Canada by its students.**Site web**:
**Intitulé du doctorat**:

- Doctorat en sciences de l'activité physique ou en génie électrique**Pays d'obtention du doctorat**:

- Canada**Etablissement délivrant le doctorat**:

- Université de SherbrookeStudents should have a minimum 80% GPA, with background in kinesiology, neuroscience, psychology, computer science or related disciplines. The positions can start anytime in 2023 or 2024.- 15/09/2023



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