We argue that hardware modularity plays a key role in the convergence of Robotics and Artificial Intelligence (AI). We introduce a new approach for building robots that leads to more adaptable and capable machines. We present the concept of a self-adaptable robot that makes use of hardware modularity and AI techniques to reduce the effort and time required to be built. We demonstrate in simulation and with a real robot how, rather than programming, training produces behaviors in the robot that generalize fast and produce robust outputs in the presence of noise. In particular, we advocate for mammals.
@article{arxiv.1802.04082,
title = {Towards self-adaptable robots: from programming to training machines},
author = {Víctor Mayoral and Risto Kojcev and Nora Etxezarreta and Alejandro Hernández and Irati Zamalloa},
journal= {arXiv preprint arXiv:1802.04082},
year = {2018}
}