Metaheuristics for Robotics. Hamouche Oulhadj

Читать онлайн книгу.

Metaheuristics for Robotics - Hamouche Oulhadj


Скачать книгу

       — vision in robotics.

      With regard to trajectory planning, the difficulties raised are related to the redundant nature of the robot being used (the manipulative arm with several degrees of freedom), the nature of the environment in which the robot evolves (the environment cluttered with obstacles, uncertainties about the environment, etc.) and of course the complexity of the task at hand (the level of accuracy required, the time allowed to perform this task, the amount of motor power needed in order to minimize consumed energy and avoid sudden movements which could deteriorate the mechanical structure of the robot). All of these parameters can induce an excessively high number of decision variables and constraints to be taken into account.

      For the control of collaborative robots (force-feedback robots designed for physical assistance in carrying out a task), the complexity of the problem resides in the almost infinite number of combinatory solutions to be tested before finding the proper values of control parameters. These must provide the desired optimal effort, within a reasonable time frame, without anachronistic movements that could endanger the person under assistance or present a risk of resonance that could deteriorate the mechanical structure of the robot. Since the automatic control system is designed to operate in an uncertain and dynamic environment, the task becomes more complex due to the servo control that operates in real time, in order to take into account external disturbances and the permanent evolution of input data (setpoints) over time.

      This book is organized into five chapters.

      Chapter 1 is a general study which reviews the mathematical foundations needed for modeling optimization problem in order to solve them using numerical methods. A list of basic methods can be found therein, including comments and a great deal of information about their characteristics and properties. This chapter is essential for understanding the approaches developed in the following chapters to solve more complex medical problems.

      Chapter 2 focuses on the application of metaheuristics in optimization problems related to robotics. Particular emphasis is placed on issues related to the fields of trajectory planning and automatic control. The challenges encountered, the difficulties that have to be overcome and the pertinence of metaheuristics for their solution in an approximate but sufficiently effective manner are described with the utmost concern for clarity. Most common general algorithms within these two areas of application are also presented in detail.

      Chapter 4 focuses on a particular aspect of trajectory planning, i.e. how smooth curves are obtained (primitive and derived curves). Based on the results produced by the method outlined in Chapter 3, the objective is to complement the latter in order to simultaneously optimize the trajectory and the dynamic behavior of the robot. For this purpose, the planning of the trajectory is reformulated in the form of a constrained optimization problem, the resolution of which resorts to a metaheuristic combining a genetic algorithm with the augmented Lagrangian method.

       — proportional action: the control error is multiplied by a gain Kp;

       — integral action: the error is multiplied by a gain Ki;

       — derivative action: the error is multiplied by a gain Kd;

      The problem to be solved being combinatory by nature and using continuous variables, the difficulty lies in the almost infinite number of solutions to be tested to find the combination of parameters Kp, Ki and Kd that would produce the appropriate control torque. The second difficulty lies in the real-time operation of the PID control, in order to take into account the external disturbances and the continuous evolution of the work requested of the robot. To overcome all these difficulties, a metaheuristic based on an algorithm making use of swarm intelligence is developed. This metaheuristic is an adaptation of the particle swarm optimization (PSO) algorithm for the purposes of the application.

      Finally, a general conclusion, given at the end of the book, briefly summarizes the problems studied and reviews the methods recommended for solving them appropriately. Development perspectives and avenues to be explored are also outlined to ultimately make use of the results in a clinical framework. This conclusion is followed by a list of bibliographic references that the reader can consult in order to deepen their understanding, if necessary, of the theoretical and practical concepts developed in this book.

      Конец ознакомительного фрагмента.

      Текст предоставлен ООО «ЛитРес».

      Прочитайте эту книгу целиком, купив полную легальную версию на ЛитРес.

      Безопасно оплатить книгу можно банковской картой Visa, MasterCard, Maestro, со счета мобильного телефона, с платежного терминала, в салоне МТС или Связной, через PayPal, WebMoney, Яндекс.Деньги,


Скачать книгу