The iCub robot is a child-like humanoid robot (see http://www.icub.org) with 53 degrees of freedom, a sensitive skin, and many sensors. A previous project made iCub crawl on the ground [1]. The goal of this master internship is to use the Intelligent Trial and Error algorithm [2] to learn a new gait when the iCub is broken (e.g. a broken cable in the elbow).
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++.
Video: https://www.youtube.com/watch?v=T-c17RKh3uE
References:
[1] Degallier, S., Righetti, L., Natale, L., Nori, F., Metta, G., & Ijspeert, A. (2008, October). A modular bio-inspired architecture for movement generation for the infant-like robot iCub. In Biomedical Robotics and Biomechatronics, 2008. BioRob 2008. 2nd IEEE RAS & EMBS International Conference on (pp. 795-800). IEEE.
[2] 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.