Robotics: Nicolas Mansard, coordinator of the MEMMO project, winner of the Stars of Europe

Created in 2013, the Stars of Europe reward the coordinators of European collaborative research projects. On December 6, Sylvie Retailleau, Minister of Higher Education and Research presented a trophy to twelve winners during a ceremony at the Quai Branly museum. Among them, Nicolas Mansard, CNRS researcher in robotics at LAAS-CNRS, holder of the ANITI chair Artificial and natural movement”, rewarded for the coordination of the MEMMO (memory of motion) project.

Funded by the Horizon 2020 program over a period of four years, MEMMO (Memory of Motion) is a collaborative project initiated in 2018 which brought together a consortium of 10 European partners for a budget of 4 million euros: the LAAS-CNRS ( France), IDIAP (Switzerland), University of Edinburgh (UK), Max-Planck Institute (Germany), University of Oxford (UK), Trento University (IT ), PAL-Robotics (Spain), Wandercraft (France), Airbus (France), Costain (UK) and APAJH (France).

Nicolas Mansard, robotics researcher in the Gepetto team of LAAS-CNRS (Movement of Anthropomorphic Systems), CNRS bronze medalist, project coordinator, declared during the ceremony:

“I would like to thank the people who helped me coordinate this project. It is a project set up by a consortium of young researchers. It was a great pride for me to be chosen to coordinate this project”.

He then added:

“We wanted to prove that it was possible to generate complex movements for arbitrary robots with arms and legs interacting in a dynamic environment in real time”.

Memorizing optimal movements

Calculating robot movements is complex and even more so for robots with arms and legs, moving in an unstructured environment.

For this project, the consortium brought together a group of experts in numerical optimization, machine learningcontrol and robot design.

Nicolas Mansard explains:

“For a walking robot to react to a situation in real time, it must solve a numerical problem with 10,000 variables in a millisecond, which is far beyond the scope of what artificial intelligence is capable of doing today. We invented Memory of Motion to meet this great challenge”.

The project team generated a massive amount of pre-calculated optimal motion offline and compressed it into a database of possible reactions called Memory of Motion.

Nicolas Mansard comments:

“We use the best motion planners available to reduce exploration time [de la base de données] and improve the quality of the data generated, and we use machine learning to encode it into motion memory, which takes less storage. Then, we optimally adapt a candidate movement of memory to similar situations that have not been explicitly explored. This is called “generalization”.

When it moves, the robot recognizes a new situation thanks to its sensors in real time. It then selects an appropriate reaction from its memory and optimizes it using its predictive abilities.

Nicolas Mansard adds:

“Online, we use this motion memory to guide an ‘optimization solver’ that makes the final decision on how the robot should behave to maintain balance, walk, manipulate tools and other things.”.

Three demonstrators validated by the proof of concept

The team has developed three demonstrators:

  • A humanoid robot to perform tooling tasks for aircraft assembly one in a factory of the future with consortium partner Airbus in Toulouse;
  • A walking exoskeleton was paired with a paraplegic patient in a rehabilitation center under medical supervision, in partnership with the APAJH federation, an association for adults and young people with disabilities. A medical center is also going to experiment with it.
  • A quadruped robot capable of walking in a tunnel being dug or in buildings to be demolished, in partnership with Costain, the British builder of the Channel Tunnel. It was also tested using an existing commercial industrial inspection robot from the Swiss company ANYbotics.

The same motion generator was used to produce three very different demonstrators thanks to numerical optimization and machine learning, the proof of concept was carried out for all three, which makes it possible to envisage future applications.

Currently the humanoid robot only exists in the laboratory, the quadruped works but is not marketed, as for the exoskeleton it is already a tool used in rehabilitation centers.

Nicolas Mansard says:

“Today the exoskeleton allows patients to work on their rehabilitation in a hospital center, but in the long term, it could replace the wheelchair”.

We want to say thanks to the author of this article for this awesome content

Robotics: Nicolas Mansard, coordinator of the MEMMO project, winner of the Stars of Europe

Our social media profiles here , as well as other pages related to them here.