• Alter-Ego
• Brain-Computer-Interface (BCI)
• Home4.0
• Point cloud filtering

This thesis work is part of the Home 4.0 project, which proposes an innovative solution for patients with various disabilities, enabling them to gain greater autonomy in daily activities through the use of robotic devices controlled by BCI (Brain-Computer Interface).

Throughout the different chapters, several implementation ideas for specific tasks that could assist patients will be explored. The goal is to make a humanoid robot autonomous and capable of recognizing the environment in which the patient lives, distinguishing different rooms, and identifying a given target specified by the user.

The robot will be able to recognize and detect various objects in the room, allowing it to retrieve and deliver them to the user when needed. To develop these tasks on the robot, various techniques have been analyzed, including object detection algorithms, point cloud filtering, object pose estimation relative to an inertial robot, grasping strategies, learning methods for different types of trajectories, and indoor navigation algorithms focused on obstacle avoidance.

To provide the user with the most intuitive experience possible, a graphical interface has been implemented to translate signals sent by BCI devices into high-level commands for the robot.