Abstract
Future trends in robotics call for robots that can work, interact and collaborate with humans. Developing these kind of robots requires the development of intelligent behaviours. As a minimum standard for behaviours to be considered as intelligent, it is required at least to present the ability to learn skills, represent skill’s knowledge and adapt and generate new skills. In this work, a cognitive framework is proposed for learning and adapting models of robot skills knowledge. The proposed framework is meant to allow for an operator to teach and demonstrate the robot the motion of a task skill it must reproduce; to build a knowledge base of the learned skills knowledge allowing for its storage, classification and retrieval; to adapt and generate new models of a skill for compliance with the current task constraints. This framework has been implemented in the humanoid robot HOAP-3 and experimental results show the applicability of the approach.
Highlights
This work is centred on the major idea of future robotic systems, humanoid robots, with the cognitive capabilities that allow them to interact with humans in their homes, workplaces and communities, providing support in several areas, and to collaborate with humans in the same unstructured working environments
In order to generate a new skill made of the combination of several robot skills models previously learned, we have developed a method for skills combination
This work is centred on the aspiration of building humanoid robots capable of interacting with humans in their homes, workplaces and communities, providing support in several areas and collaborating with humans in the same unstructured working environments
Summary
This work is centred on the major idea of future robotic systems, humanoid robots, with the cognitive capabilities that allow them to interact with humans in their homes, workplaces and communities, providing support in several areas, and to collaborate with humans in the same unstructured working environments. A framework is proposed for the learning, generation and adaptation of robot skill models for complying with task constraints.
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