Internship (M/F): co-design of exoskeletons using AI & optimization methods Full-time

Contexte et atouts du poste

Context and funding:

The position is funded by the PEPR O2R, a national French program to advance research in robotics which reunites several French laboratories in robotics, AI, and Social and Human Sciences.

In this context, the HUCEBOT team is involved in the projects AS3 and PI3, with the challenge to design AI-powered controllers for exoskeletons for improved assistance.

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 prediction and control techniques for wearable exoskeletons designed to assist humans at work. 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.

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 and expat community.

Mission confiée

The internship is about optimizing the kinematics and dynamics properties of an exoskeleton using AI and numerical optimization methods. The idea is to design an automated workflow to: 1) find a suitable parameterization of an exoskeleton design / prototype, and 2) optimize its parameters to either be the most performing for a specific task, or to be the average best performing for a number of different tasks. The parametrization can include the mechatronics design of the robot, its physical limits, its dynamics, the actuation, the contacts with the human body, and even the human body morphology as well can be object of the optimization loop. The workflow must include the validation of the generated parameters (and therefore exoskeleton) on a simulated physical environment, where the generated exoskeleton (defined in a URDF model) is physically attached to a rigid body model representing a simplified human. To optimize the parameters, we will investigate classical reinforcement learning based methods, evolutionary optimization methods, and generative AI methods that leverage the textual description of the exoskeleton in URDF. The co-design workflow should consider also human-in-the-loop feedback, so that the human can validate the final design.

The goal of the internship is to find a new optimized design of an exoskeleton starting from the initial protoype..

The internship is for up to 6 months.

Principales activités

• Review state of the art in co-design of exoskeletons and robots
• Review methods of numerical optimization of parametrized designs and generative AI for hardware design
• Implementing parametrized description of exoskeletons
• Design and write software algorithms for co-design
• Write hardware/software report
• Collaborate with the team to integrate the co-design workflow in the current experiments and developments

Compétences

• Technical skills:
• Very good programming skills (python, C++).
• Background in mechatronics or ability to understand mechanical design
• Excellent skills and/or experience with evolutionary optimization, numerical optimization, and/or generative AI models.
• Soft skills:
• Excellent communication skills at work, and ability to report progress
• Proactivity.
• 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