机器人任务的分解模型

Salima Benbernou
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引用次数: 1

摘要

赋予机器人执行非重复性任务(未完全定义的任务称为意外任务)的能力的程序的植入受到一个复杂问题的阻碍:经典方法在编程(程序)中遇到困难,以制定进化模型不服从算法预先建立的设计。作为其中的一部分,本文的目的是提出一种基于复杂任务分解机制的分析方法。这个想法包括将编程活动细分为两个步骤。一种描述性步骤,允许使用功能方法制定复杂任务,而不将任何元素集成到执行程序的构造中;一种建设性步骤,使用前面的公式开发程序。这个程序或多或少明确地表达了在机器人级别执行任务时解决不同问题的方法。在执行任务时,时间方面作为逻辑形式在最后一步中引入,用于对操作进行排序。
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A factorisation model of robotic tasks

The implantation of programs which gives a robot the ability to perform a non-repetitive task (task not completely defined called also unexpected), was hindered by a complex problem: the difficulty met by the classical method in programming (procedural) to formulate a task which the evolution model does not obey to an algorithmic pre-established design. As a part of that the aim of this paper is to propose an analysis approach which lies on a mechanism of factorisation of the complex task. The idea developed consists of subdividing the activity of programming into two steps. A descriptive step which allows the formulation of a complex task using a functional approach without integrating any element to the construction of an executing program and a constructive step which develops a program using the preceding formulation. This program expresses, more or less explicitly, the way of solving different problems posed by the execution of the task at the level of a robot. The aspect of time is introduced as a logical form in the last step for the sequencing of actions while executing a task.

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Volume Contents Simulating behaviors of human situation awareness under high workloads Emergent synthesis of motion patterns for locomotion robots Synthesis and emergence — research overview Concept of self-reconfigurable modular robotic system
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