Metaheuristics for Robotics. Hamouche Oulhadj
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Название: Metaheuristics for Robotics

Автор: Hamouche Oulhadj

Издательство: John Wiley & Sons Limited

Жанр: Программы

Серия:

isbn: 9781119706991

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      Riad MENASRI

      November 2019

      Introduction

      This work is part of a collection of books, published by ISTE and Wiley, devoted to metaheuristics and their applications. Known for being specific and particular algorithms, what practical interest do metaheuristics have to make them increasingly attractive to engineers, researchers and scientists from various areas interested in different fields of application? There are two important arguments that provide us with obvious answers: on the one hand, the scope of application of metaheuristics is constantly gaining momentum, without apparently being concerned with any limitations; on the other hand, these resolution methods possess a high level of abstraction, which makes them adaptable to a wide range of engineering problems. Furthermore, a small number of necessary adjustments that do not change the nature of algorithms are usually sufficient to solve new optimization problems without any particular links existing between them.

      In practice, there may be several existing solutions to an optimization problem, of which only one of these solutions is generally optimal. All others are suboptimal solutions, but are still eligible, so-called acceptable, solutions because they guarantee the completion of an objective without violating associated constraints. However, the notion of optimizing acceptability may appear to be overly abstract: how can the level of solution operability be identified when the level of appreciation of that solution may vary not only from one user to another, but also with the margin of error tolerated by each type of application? Clearly, there is no absolute answer to this question, because it is ultimately each individual who decides how to define the level of acceptability for a solution, based on individual needs and the quality of the results sought for the application to be addressed.

      Today, metaheuristics have become almost unavoidable in numerous areas of engineering due to the difficulties that have to be overcome to properly solve common optimization problems. These difficulties generally lie in the complex nature of the systems under study: the number of constraints and decision variables to be taken into account can be very high, computational times can be very long and non-differentiable objective functions can be highly multimodal or even too complex to be mathematically formalized with accuracy. The field of robotics is by nature a very broad field of application. In fact, these very relevant algorithms can be found in many applications of robotics:

       — trajectory planning for mobile robots;

       — robust control of portable robots for motion assistance;

       — cooperation tasks between robots;

       — 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.

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