Robotics has been quickly increasing its importance in our society over the last decade, both at an industrial level (Industry 4.0) and at a service level (Society 5.0). This progressive implantation of robots in the different parts of our daily lives brings the need for a major boost in research, innovation and transfer in all scientific fields directly related to robotics, with the synergies between robotics and artificial intelligence becoming increasingly important for the advancement of this discipline.
Within this field, two of the most important elements for increasing the capabilities of robots are the ability to manipulate objects (robotic manipulation) and the ability to interact naturally and directly with humans (human-robot interaction). Robots (mobile, articulated arms or articulated arms on mobile platforms) used in industrial and service applications must be better adapted to their environment by developing new multi-modal control strategies (based on visual, force, tactile information, etc.) in order to be able to manipulate objects (especially deformable objects) in collaborative tasks with humans. For the development of these capabilities, progress in consensus and distributed learning algorithms is particularly relevant, as well as the adjustment of learned models over time. Also, the improvement of artificial vision capabilities that allow robots to recognise scenes and identify characteristics of the environment, to process gestures and interpret actions in order to facilitate the interaction of these systems with humans. Likewise, the development of capabilities that improve the autonomy and advanced navigation of robots in complex, unstructured or predefined environments.
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