| dc.description.abstract | The main goal of this dissertation is to propose, to test and to evaluate the use of Machine Learning (ML) techniques in the automatic con_guration of the gait control in legged robots. In order to achieve this goal, an extensive research about state-of-the-art techniques was accomplished and they are described in this work. This research allowed the development of the proposed model, called LegGen, which was implemented in a prototype. The proposed model allows the use of several different robot models with four, six or more paws. Besides that, the prototype allows also to study the robot's morphology evolution. The implemented prototype allows to accomplish experiments with autonomous legged robots, in a realistic three-dimensional virtual environment, through physics based simulations. The ODE (Open Dynamics Engine) software library was used in the physical simulation of rigid bodies and articulations, allowing to simulate forces acting in the articulations (actuators), gravity and collisions, among other | en |
