Автоматический синтез сценариев походки реконфигурируемых мехатронно-модульных роботов в модификации шагающей платформы

摘要

Reconfigurable mechatronic modular robots capable of adapting their structure depending on the specifics of the tasks performed and the environmental conditions are of great interest for a wide range of different applications. One of the key issues in controlling the movement of robots of this type is the need to use original algorithms for each of the possible configurations. The variety of configurations is determined by the structure of mechatronic modules, their number and the selected connection option. Some typical configurations of mechatronic modular robots allow the development of motion control algorithms invariant with respect to the number of modules in the kinematic structure. However, a promising approach to solving the problem is generally associated with the development of self-learning methods and tools for the automated synthesis of motion control algorithms of a multi-link mechatronic modular robot in case of chosen configuration. This article discusses the results of research on the use of self-organized finite-state machines for solving the problem of automatic synthesis of scenarios for the gait of reconfigurable mechatronic-modular robots in the modification of the walking platform. The results of model experiments confirming the efficiency and effectiveness of the developed algorithms are presented.