Context-Aware Exoskeleton Shared-Control With Human-In-The-Loop Adaptation H/F INRIA

Context-aware exoskeleton shared-control with human-in-the-loop adaptation
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : Stage

Niveau de diplôme exigé : Bac +4 ou équivalent

Fonction : Stagiaire de la recherche

Contexte et atouts du poste

Context and funding:
This position is funded by thePEPR O2R / PI3 project.
Within this framework, the HUCEBOT team isdeveloping multimodal strategies for online control and adaptation of exoskeletons. The team has already developed some prototypes of active exoskeletons (1dof, 2 dof) for the upper-body assistance, and has conducted user studies to identify the contribution of AI-based models to trasparency and assistance in presence of payloads. The challenge here is to use additional sources of information to adapt online the control parameters, to take into ccount the context and the human preferencesand feedback. This internship is at the cross among multimodal interaction, shared control and human-in-the-loop adaptation.

About the team:
The candidate will join the Human Centered Robotics team (HUCEBOT) in the Inria Center of the University of Lorraine in Nancy, France.
The team HUCEBOT develops control, learning, and interaction skills of human-centered robots, such as humanoid, mobile manipulators and exoskeletons. The team develops learning and control algorithms for teleoperated / supervised / autonomous robots, involved in complex manipulation tasks in man-made environments. It also develops AI-based control for wearable exoskeletons designed to assist humans at work, drones and quadrupeds to explore complex environments. The team has excellent robotics facilities, including several humanoid robots (Talos, iCub, G1), manipulators, drones, passive and active exoskeletons, wearable sensors, force plates etc. Its laboratory has a 3D printing facility and a mechatronic workshop for prototyping and maintenance, and a motion capture room with Qualisys and Xsens sensors.
The team consists of many research scientists, postdocs, PhD and has the support of 1 software and 1 mechatronics engineer. The team is international - English and French speaking. French is not required, although free French classes are available in the institute for non-French speakers.

About the laboratory and Nancy:
The Inria Center of the University of Lorraine, is co-located with the Loria laboratory, in the Science and Technology Campus of the University of Lorraine (Nancy, France), next to the Botanical Gardens, at 20 minutes by public transportation or bike from the Nancy train station and City Center. Several student residences and facilities are at walking distance. Nancy is a University town, with a high quality of life and a vibrant student, Erasmus and expat community. Life is Nancy is very affordable compared to Paris, it is easy to find a student residence or apartment. Team members can also access to SUAPS, the University's sports facilities.

About Nancy in France:
Nancy is the capital of the Grand Est region in France. It is well connected by train to Paris (90 min), Strasbourg (90 min), Luxembourg and Germany. There are direct trains from Nancy to the Paris airport CDG and the Luxembourg airport LUX.
The region around Nancy is ideal for outdoor activities: there are many country trails, long bike trails, forests, mountains, lakes, ski in winter too.

Mission confiée

Upper-limb exoskeletons are increasingly used to assist humans in industrial, rehabilitation, and daily-life tasks. However, ensuring intuitive and seamless collaboration between the user and the exoskeleton remains a major challenge. Traditional control strategies often rely solely on physical signals such as EMG, which can be noisy and user-dependent or model-based methods often lack adaptability.
The goal of this internship is the development and test of innovative shared-control strategies for active upper-limb exoskeleton. For optimal user assistance, understanding of the user's goal and intention is crucial. In co-manipulation tasks between user's, speaking and looking at visual cues are essential to help the workers fulfill their common goal. The same idea can be applied to exoskeleton: equipped with vision and language, the exoskeleton should become an assistant that could be guided through voice and vision. The student will explore how multimodal information (voice + vision + physical interaction) can be fused to improve human-exoskeleton interaction. Particular attention will be devoted to online adaptation mechanisms, to be used to adapt some parameters depending on the user's feedback.
The internship is for a 4 to 6 months period and must terminate before mid-July.

The candidate will collaborate with Serena Ivaldi (researcher), Pauline Maurice (researcher) andAlexandre Oliveira Souza (postdoc).

Principales activités

- Review state of the art in shared-control approaches in human-robot interaction and exoskeleton control, particularly online adaptation algorithms.
- Familiarize with state-of-the-art modules for voice recognition and vision-based perception (some already in the team).
- Participate to the design and implementation of shared control schemes blending human inputs with autonomous exoskeleton actions.
- Carry out experiments to validate the developed approaches in user experiments.
- Analyze results and write reports.
- Collaborate with the team on the current experiments and developments
- Participate in the team and the project's relevant activities and events

Compétences

- Technical skills:
- Background in robotics, control, or human-robot interaction.
- Excellent skills and/or experience with Python/C++ (AI frameworks such as Torch/Tensorflow is a plus)
- Interest and preferably experience with assistive robotics and human experiments.
- Soft skills:
- Excellent communication skills at work, and ability to report progress
- Not afraid of challenging projects.
- Rigour and intellectual honesty
- Curiosity and desire to learn
- Practical mindset and ability to develop robust and reliable solutions
- Autonomy and organizational skills
- Love working in a multi-cultural environment
- Team player

Avantages

- Subsidized meals
- Partial reimbursement of public transport costs
- Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
- Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage

Rémunération

€4.35/hour