GA Optimization of an Hexapod Robot Parameters for Periodic Gaits

Different strategies have been adopted for the optimization of legged robots, either during their design and construction phases, or during their operation. Evolutionary strategies are a way to "imitate nature" replicating the process that nature designed for the generation and evolution of species. This paper presents a genetic algorithm, running over a simulation application of legged robots, allowing the optimization of several locomotion, model and controller parameters, for different locomotion speeds and hexapod periodic gaits. Here are studied the model and locomotion parameters that optimize the robot performance, in a large range of distinct velocities, when the robot walks with distinct periodic gaits.N/

A literature review on the optimization of legged robots

Over the last two decades the research and development of legged locomotion robots has grown steadily. Legged systems present major advantages when compared with ‘traditional’ vehicles, because they allow locomotion in inaccessible terrain to vehicles with wheels and tracks. However, the robustness of legged robots, and especially their energy consumption, among other aspects, still lag behind mechanisms that use wheels and tracks. Therefore, in the present state of development, there are several aspects that need to be improved and optimized. Keeping these ideas in mind, this paper presents the review of the literature of different methods adopted for the optimization of the structure and locomotion gaits of walking robots. Among the distinct possible strategies often used for these tasks are referred approaches such as the mimicking of biological animals, the use of evolutionary schemes to find the optimal parameters and structures, the adoption of sound mechanical design rules, and the optimization of power-based indexes

Efficient Evolution of Neural Networks

This thesis addresses the study of evolutionary methods for the synthesis of neural network controllers. Chapter 1 introduces the research area, reviews the state of the art, discusses promising research directions, and presents the two major scientific objectives of the thesis. The first objective, which is covered in Chapter 2, is to verify the efficacy of some of the most promising neuro-evolutionary methods proposed in the literature, including two new methods that I elaborated. This has been made by designing extended version of the double-pole balancing problem, which can be used to more properly benchmark alternative algorithms, by studying the effect of critical parameters, and by conducting several series of comparative experiments. The obtained results indicate that some methods perform better with respect to all the considered criteria, i.e. performance, robustness to environmental variations and capability to scale-up to more complex problems. The second objective, which is targeted in Chapter 3, consists in the design of a new hybrid algorithm that combines evolution and learning by demonstration. The combination of these two processes is appealing since it potentially allows the adaptive agent to exploit a richer training feedback constituted by both a scalar performance objective (reinforcement signal or fitness measure) and a detailed description of a suitable behaviour (demonstration). The proposed method has been successfully evaluated on two qualitatively different robotic problems. Chapter 4 summarizes the results obtained and describes the major contributions of the thesis

Optimização dos parâmetros de um robô hexápode através de algoritmos genéticos

Mestrado em Engenharia Electrotécnica e de ComputadoresOs robôs com pernas apresentam vantagens significativas quando comparados com os veículos tradicionais que apresentam rodas e lagartas. A sua maior vantagem é o facto de permitirem a locomoção em terrenos inacessíveis a outro tipo de veículos uma vez que não necessitam de uma superfície de suporte contínua. No entanto, no estado de desenvolvimento em que se encontram, existem vários aspectos que têm que ser necessariamente melhorados e optimizados. Tendo esta ideia em mente, têm sido propostas e adoptadas diferentes estratégias de optimização a estes sistemas, quer durante a fase de projecto e construção, quer durante a sua operação. Entre os critérios de optimização seguidos por diferentes autores podem- -se incluir aspectos relacionados com a eficiência energética, estabilidade, velocidade, conforto, mobilidade e impacto ambiental. As estratégias evolutivas são uma forma de “imitar a natureza” replicando o processo que a natureza concebeu para a geração e evolução das espécies. O objectivo deste trabalho passa por desenvolver um algoritmo genético, sobre uma aplicação de simulação de robôs com pernas já existente e desenvolvida em linguagem C, que permita optimizar diferentes parâmetros do modelo do robô e do seu padrão de locomoção para diferentes velocidades de locomoção.Legged robots have significant advantages when compared with traditional vehicles using wheels and tracks. Their biggest advantage is that they allow the locomotion on terrains inaccessible to other type of vehicles because they don’t need a continuous support surface. However, in their actual stage of development, there are several aspects that must necessarily be improved and optimized. With these ideas in mind, different strategies have been proposed and adopted for the optimization of these systems, either during their design phase and construction, or during their operation. Among the different optimization criteria followed by different authors, it is possible to find issues related to energy efficiency, stability, speed, comfort, mobility and environmental impact. Evolutionary strategies are a way to "imitate nature" replicating the process that nature designed for the generation and evolution of species. The objective of this project is the development of a genetic algorithm, running over a simulation application of legged robots, already developed in C, which allows the optimization of various parameters of the robot model and of its gaits for different locomotion speeds