This book contains an edited collection of eighteen contributions on soft and hard computing techniques and their applications to autonomous robotic systems. Each contribution has been exclusively written for this volume by a leading researcher. The volume demonstrates the various ways that the soft computing and hard computing techniques can be used in different integrated manners to better develop autonomous robotic systems that can perform various tasks of vision, perception, cognition, thinking, pattern recognition, decision-making, and reasoning and control, amongst others. Each chapter of the book is self-contained and points out the future direction of research.

"It is a must reading for students and researchers interested in exploring the potentials of the fascinating field that will form the basis for the design of the intelligent machines of the future"
(Madan M. Gupta)

This book contains an edited collection of eighteen contributions on soft and hard computing techniques and their applications to autonomous robotic systems. Each contribution has been exclusively written for this volume by a leading researcher. The volume demonstrates the various ways that the soft computing and hard computing techniques can be used in different integrated manners to better develop autonomous robotic systems that can perform various tasks of vision, perception, cognition, thinking, pattern recognition, decision-making, and reasoning and control, amongst others. Each chapter of the book is self-contained and points out the future direction of research.

"It is a must reading for students and researchers interested in exploring the potentials of the fascinating field that will form the basis for the design of the intelligent machines of the future"
(Madan M. Gupta)

This work study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed.