This book focuses on the efficient performance of mobile robots through the use of multi-hierarchical symbolic representations of the environment.

A mobile robot intended to perform deliberative actions must possess some symbolic representation of its workspace, but such representations of real environments usually become so large that should be conveniently arranged in order to facilitate and, in some cases, make possible their use.

Apart from the drawback of dealing with large amounts of information, other problems stand out when using symbolic representations. One is keeping the model properly optimized with respect to the robot tasks while maintaining it coherent with reality. Another one is the creation (or modification) of symbols from sensorial data.

This book addresses all these issues considering symbolic multi-hierarchical structures. Such structures, based on the concept of abstraction, allow a robot to speed up its operation in large environments. Practical solutions tested on real robots (for instance, a robotic wheelchair for elder people) are provided.

The book is intended for PhD students and in general for robotics, computer science, and artificial intelligence researchers.

Klappentext

This book focuses on the performance of mobile robots through the use of multi-hierarchical symbolic representations of the environment.

To perform deliberative actions, a robot must possess some symbolic representation of its workspace, but representations of real environments can become so large that they must be conveniently arranged to facilitate and, in some cases, make possible their use. Practical solutions tested on real robots, for example a robotic wheelchair, are provided.

Inhalt

A Robotic Future.- Multi-Hierarchical, Symbolic Representation of the Environment.- Application of Hierarchical Models to Mobile Robot Task Planning.- Mobile Robot Operation with Multi-Hierarchies.- Automatic Learning of Hierarchical Models.- Implementation and Experiences on a Real Robot.