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This overview of the problems formulations for robotic manipulators at different abstraction levels can be used to find the causes of troubles with some types of control systems. For many variants of manipulators, for example, biomorphic ones, it is not yet possible to achieve the required quality and universality. Nevertheless these tasks are solvable, which is proved by the natural movement control systems of biological organisms. One of the reasons of the difficulties is the complexity of the formalization of motion control, which prevents the development of universal approaches. The existing formalizations were separated by functional level to facilitate analysis. The high-level problems (the division of complex motor tasks into stages) are successfully solved by general planners or logical inference procedures. The middle-level problems (the trajectory tracing according to an abstract motor task) are so far solved less efficiently. Some existing tools, as linguistic methods, can greatly facilitate solution, but require significant and very laborious formalization of conditions. Inverse problems of kinematics and dynamics, conjugation of trajectory sections and direct control of the manipulator motors with error handling are further stages of processing; the quality of known solutions is usually acceptable. Based on the data collected, it can be argued that the development of methods for solving medium-level problems, i.e. constructing the trajectory of the robot according to the description of the action, is the most important domain for the successful creation of new types of manipulator control systems.
This overview of the problems formulations for robotic manipulators at different abstraction levels can be used to find the causes of troubles with some types of control systems. For many variants of manipulators, for example, biomorphic ones, it is not yet possible to achieve the required quality and universality. Nevertheless these tasks are solvable, which is proved by the natural movement control systems of biological organisms. One of the reasons of the difficulties is the complexity of the formalization of motion control, which prevents the development of universal approaches. The existing formalizations were separated by functional level to facilitate analysis. The high-level problems (the division of complex motor tasks into stages) are successfully solved by general planners or logical inference procedures. The middle-level problems (the trajectory tracing according to an abstract motor task) are so far solved less efficiently. Some existing tools, as linguistic methods, can greatly facilitate solution, but require significant and very laborious formalization of conditions. Inverse problems of kinematics and dynamics, conjugation of trajectory sections and direct control of the manipulator motors with error handling are further stages of processing; the quality of known solutions is usually acceptable. Based on the data collected, it can be argued that the development of methods for solving medium-level problems, i.e. constructing the trajectory of the robot according to the description of the action, is the most important domain for the successful creation of new types of manipulator control systems.
Актуальность работы обусловлена актуализацией методов решения обратной задачи кинематики применительно к различным кинематическим структурам (формациям) реконфигурируемых модульных систем. Цель работы заключается в анализе методов решения обратной задачи кинематики, которые возможно применить к различным формациям самореконфигурируемых многозвенных робототехнических систем. Проведено исследование прямой кинематики различных формаций модульных робототехнических систем на основе ранее полученных результатов исследований других ученых. Выполнен анализ методов решения обратной задачи кинематики модульных реконфигурируемых систем и произведена оценка их возможного применения для различных кинематических структур модульных систем. Рассмотрены аналитические и численные методы решения, приведены примеры практического применения. Кроме того, в работе проведен анализ различных методов машинного обучения. По результатам исследования выделены преимущества и недостатки различных методов решения обратной задачи кинематики модульных робототехнических систем. Выделены потенциально подходящие методы решения данной задачи с точки зрения вычислительной сложности, возможности применения для систем с избыточным числом степеней свободы. Среди исследованных методов зачастую рассматриваются частные решения обратной задачи кинематики. В результате проведенного анализа можно выделить направления исследований, связанные с разработкой методов машинного обучения, которые потенциально подходят для применения в задачах управления самореконфигурируемыми модульными робототехническими системами. Разработка такого метода позволит снизить количество предварительных аналитических расчетов, реализовать систему управления, которая не потребует существенных изменений алгоритмов, а также расширить возможности применения модульных систем за счет адаптации данной системы к поверхности передвижения. The relevance of this work is due to the actualization of methods for solving the inverse kinematics in relation to various kinematic structures (formations) of reconfigurable modular systems. The purpose of the work is to analyze methods for solving the inverse kinematics, which can be applied to various formations of self-configuring multilink robotic systems. A study of the forward kinematics of modular robotic systems various formations is conducted on the basis of the previously obtained research results of other scientists. The analysis of methods for solving the inverse kinematics of modular reconfigurable systems was carried out and an assessment of their possible application for various kinematic structures of modular systems was made. Analytical and numerical methods of solution were considered, and examples of practical application were also given. In addition, the paper analyzed various machine learning methods. With regard to the results of the study, the advantages and disadvantages of various methods for solving the inverse kinematics of modular robotic systems were highlighted. Potentially suitable methods for solving this problem from the point of view of computational complexity and application possibilities for systems with a redundant number of degrees of freedom are identified. Among the methods considered, particular solutions of the inverse kinematics of a certain modular reconfigurable system kinematic structure are often evaluated. As a result of the analysis, it is possible to isolate areas of research related to the development of machine learning methods that are potentially suitable for use in control problems for self-reconfiguring modular robotic systems. The development of such a method will enable to reduce the number of preliminary analytical calculations, to implement a control system that does not require significant changes in algorithms, and also to expand the possibilities of using modular systems by adapting this system to the movement surface.
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