Evolutionary optimization of a bipedal gait in a physical robot,”

Abstract-Evolutionary optimization of a gait for a bipedal robot has been studied, combining structural and parametric modifications of the system responsible for generating the gait. The experiment was conducted using a small 17 DOF humanoid robot, whose actuators consist of 17 servo motors. In the approach presented here, individuals representing a gait consisted of a sequence of set angles (referred to as states) for the servo motors, as well as ramping times for the transition between states. A hand-coded gait was used as starting point for the optimization procedure: A population of 30 individuals was formed, using the hand-coded gait as a seed. An evolutionary procedure was executed for 30 generations, evaluating individuals on the physical robot. New individuals were generated using mutation only. There were two different mutation operators, namely (1) parametric mutations modifying the actual values of a given state, and (2) structural mutations inserting a new state between two consecutive states in an individual. The best evolved individual showed an improvement in walking speed of approximately 65%

Climbing and Walking Robots

With the advancement of technology, new exciting approaches enable us to render mobile robotic systems more versatile, robust and cost-efficient. Some researchers combine climbing and walking techniques with a modular approach, a reconfigurable approach, or a swarm approach to realize novel prototypes as flexible mobile robotic platforms featuring all necessary locomotion capabilities. The purpose of this book is to provide an overview of the latest wide-range achievements in climbing and walking robotic technology to researchers, scientists, and engineers throughout the world. Different aspects including control simulation, locomotion realization, methodology, and system integration are presented from the scientific and from the technical point of view. This book consists of two main parts, one dealing with walking robots, the second with climbing robots. The content is also grouped by theoretical research and applicative realization. Every chapter offers a considerable amount of interesting and useful information

Humanoid Robots

For many years, the human being has been trying, in all ways, to recreate the complex mechanisms that form the human body. Such task is extremely complicated and the results are not totally satisfactory. However, with increasing technological advances based on theoretical and experimental researches, man gets, in a way, to copy or to imitate some systems of the human body. These researches not only intended to create humanoid robots, great part of them constituting autonomous systems, but also, in some way, to offer a higher knowledge of the systems that form the human body, objectifying possible applications in the technology of rehabilitation of human beings, gathering in a whole studies related not only to Robotics, but also to Biomechanics, Biomimmetics, Cybernetics, among other areas. This book presents a series of researches inspired by this ideal, carried through by various researchers worldwide, looking for to analyze and to discuss diverse subjects related to humanoid robots. The presented contributions explore aspects about robotic hands, learning, language, vision and locomotion

Evolutionary optimization of a bipedal gait in a physical robot

Abstract-Evolutionary optimization of a gait for a bipedal robot has been studied, combining structural and parametric modifications of the system responsible for generating the gait. The experiment was conducted using a small 17 DOF humanoid robot, whose actuators consist of 17 servo motors. In the approach presented here, individuals representing a gait consisted of a sequence of set angles (referred to as states) for the servo motors, as well as ramping times for the transition between states. A hand-coded gait was used as starting point for the optimization procedure: A population of 30 individuals was formed, using the hand-coded gait as a seed. An evolutionary procedure was executed for 30 generations, evaluating individuals on the physical robot. New individuals were generated using mutation only. There were two different mutation operators, namely (1) parametric mutations modifying the actual values of a given state, and (2) structural mutations inserting a new state between two consecutive states in an individual. The best evolved individual showed an improvement in walking speed of approximately 65%