Everything about evolutionary computation in practice
Researchers have obtained robots that display an amazing slew of behaviors and perform a multitude of tasks, including perception of environment, negotiating rough terrain, and pushing boxes. This volume offers a wide spectrum of sample works developed in leading research throughout the world about evolutionary mobile robotics and demonstrates the success of the technique in evolving efficient and capable mobile robots.
|Mobile robotic is a recent ?eld that has roots in many engineering and science disciplines such as mechanical, electrical, mechatronics, cognitive and social sciences just to name few. A mobile robot needs e?cient mechanisms of lo- motion, kinematics, sensors data, localization, planning and navigation that enable it to travel throughout its environment. Scientists have been fascinated by conception of mobile robots for many years. Machines have been designed withwheelsandtracksorotherlocomotion devicesand/orlimbs topropelthe unit. When the environment is well ordered these machines can function well. Mobile robots have demonstrated strongly their ability to carry out useful work. Intelligent robots have become the focus of intensive research in the last decade. The ?eld of intelligent mobile robotics involves simulations and re- world implementations of robots which adapt themselves to their partially unknown, unpredictable and sometimes dynamic environments. The design and control of autonomous intelligent mobile robotic systems operatinginunstructuredchangingenvironmentsincludesmanyobjectived- ?culties. There are several studies about the ways in which, robots exhibiting some degree of autonomy, adapt themselves to ?t in their environments. The application and use of bio-inspired techniques such as reinforcement lea- ing, arti?cial neural networks, evolutionary computation, swarm intelligence and fuzzy systems in the design and improvement of robot designs is an em- gentresearchtopic. Researchershaveobtainedrobotsthatdisplayanamazing slew of behaviours and perform a multitude of tasks.
Evolutionary Mobile Robots.- Differential Evolution Approach Using Chaotic Sequences Applied to Planning of Mobile Robot in a Static Environment with Obstacles.- Evolving Modular Robots for Rough Terrain Exploration.- Evolutionary Navigation of Autonomous Robots Under Varying Terrain Conditions.- Aggregate Selection in Evolutionary Robotics.- Evolving Fuzzy Classifier for Novelty Detection and Landmark Recognition by Mobile Robots.- Learning Mobile Robots.- Reinforcement Learning for Autonomous Robotic Fish.- Module-based Autonomous Learning for Mobile Robots.- A Hybrid Adaptive Architecture for Mobile Robots Based on Reactive Behaviours.- Collaborative Robots for Infrastructure Security Applications.- Imitation Learning: An Application in a Micro Robot Soccer Game.
The design and control of autonomous intelligent mobile robotic systems operating in unstructured changing environments includes many objective difficulties. There are several studies about the ways in which, robots exhibiting some degree of autonomy, adapt themselves to fit in their environments. The application and use of bio-inspired and intelligent techniques such as reinforcement learning, artificial neural networks, evolutionary computation and so forth in the design and improvement of robot designs is an emergent research topic. Researchers have obtained robots that display an amazing slew of behaviours and perform a multitude of tasks. These include perception of environment, planning and navigation in rough terrain, pushing boxes, negotiating an obstacle course, etc.
In this context, mobile robots designed using evolutionary computation approaches, usually known as Mobile Evolutionary Robotics, have experienced significant development in the last decade. The fundamental goal of mobile evolutionary robotics is to apply evolutionary computation methods to automate the production of complex behavioural robotic controllers.
This volume offers a wide spectrum of sample works developed in leading research throughout the world about evolutionary mobile robotics and demonstrates the success of the technique in evolving efficient and capable mobile robots.
Inhaltsverzeichnis
Evolutionary Mobile Robots.- Differential Evolution Approach Using Chaotic Sequences Applied to Planning of Mobile Robot in a Static Environment with Obstacles.- Evolving Modular Robots for Rough Terrain Exploration.- Evolutionary Navigation of Autonomous Robots Under Varying Terrain Conditions.- Aggregate Selection in Evolutionary Robotics.- Evolving Fuzzy Classifier for Novelty Detection and Landmark Recognition by Mobile Robots.- Learning Mobile Robots.- Reinforcement Learning for Autonomous Robotic Fish.- Module-based Autonomous Learning for Mobile Robots.- A Hybrid Adaptive Architecture for Mobile Robots Based on Reactive Behaviours.- Collaborative Robots for Infrastructure Security Applications.- Imitation Learning: An Application in a Micro Robot Soccer Game.
Klappentext
Researchers have obtained robots that display an amazing slew of behaviors and perform a multitude of tasks, including perception of environment, negotiating rough terrain, and pushing boxes. This volume offers a wide spectrum of sample works developed in leading research throughout the world about evolutionary mobile robotics and demonstrates the success of the technique in evolving efficient and capable mobile robots.
Everything about evolutionary computation in practice
Includes supplementary material: sn.pub/extras
