In our recent work (Cully et al., Nature, 2015 / see the video below), we demonstrated how a 6-legged robot can recover from an unforeseen damage conditions in less than 2 minutes. This novel machine learning algorithm opens many new possibilities to make robots more reliable and, overall, more adaptive.
Nevertheless, we used so far a very basic, open-loop controller (because our work was focused on the adaptation abilities). Our 6-legged robot is therefore unable to walk on rough terrains. To improve the robustness of our controllers, we recently added a 3D force sensor (OptoForce) on each foot of the robot, as well as a high-performance IMU.
The first objective of this internship is to implement a reactive controller that makes use of these new sensor and thus improve the gait of the robot. The controller will be based on cartesian central pattern generator with sensor feedback [2].
The second objective is to test how using this controller affects the "Intelligent Trial and Error Algorithm" [1], which allows our robot to learn new gaits when needed.
The sucessful applicant will design new experiments and new algorithms to answer these questions. He/she will have access to the facilities of the lab (two 6-legged robots, Optitrack motion capture system, etc.) and he/she will be integrated in a highly-motivated team dedicated to leveraging trial-and-error learning to make robots that can adapt to anything (see: http://www.resibots.eu).
The ideal applicant loves robots. He/she has an appetite for machine learning algorithms and (modern) C++.
<b>Video:</b> <a href="https://www.youtube.com/watch?v=T-c17RKh3uE">https://www.youtube.com/wa…;
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<strong>References:</strong>
<p>[1] Cully, Antoine, Jeff Clune, Danesh Tarapore, and Jean-Baptiste Mouret. “Robots That Can Adapt like Animals.” Nature 521, no. 7553 (May 27, 2015): 503–7. doi:10.1038/nature14422.</p>
<p>[2] Barasuol, V., J. Buchli, C. Semini, M. Frigerio, E.R. De Pieri, and D.G. Caldwell. “A Reactive Controller Framework for Quadrupedal Locomotion on Challenging Terrain.” In 2013 IEEE International Conference on Robotics and Automation (ICRA), 2554–61, 2013. doi:10.1109/ICRA.2013.6630926.</p>
<strong>POUR POSTULER</strong>
Envoyer e-mail + lettre de motivation à jean-baptiste.mouret@inria.fr
<strong>Informations supplémentaires</strong>
http://pages.isir.upmc.fr/~mouret/