Artificial systems and complex behaviours

A. Martinengo, M. Campani, V. Torre
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引用次数: 3

Abstract

This paper describes some experiments on control strategies of a mobile robot. The robot has a simple vision system and moves in a simplified world, but the controlling architecture performs tasks of increasing complexity, such as the exploration of a maze, the recovery of its structure and the planning of some nearly optimal trajectories through the maze. There are three layers of control of robot motion: the lowest layer analyses images, controls the speed of robot wheels and is essentially an optomotor reflex; the second layer has a short term memory and operates when the visual information is not complete or when the robot has lost its way; the third layer has a long term memory and reasoning capabilities, monitors the achievement of robot tasks and schedules the timing of completion of the different tasks. The vision and motor systems and other supervising units are assumed to be finite state automata and the control architecture is based on transitions between states of these automata. The control system is flexible and new capabilities are easily acquired by simply introducing new states. The intelligent behaviour of this artificial system is primarily caused by the memory and the capability to create simple and useful representations of the world.<>
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人工系统和复杂行为
本文介绍了移动机器人控制策略的一些实验。机器人有一个简单的视觉系统,并在一个简化的世界中移动,但控制架构执行越来越复杂的任务,如探索迷宫,恢复其结构和规划一些通过迷宫的接近最优轨迹。机器人运动的控制有三层:最低层分析图像,控制机器人轮子的速度,本质上是一种视运动反射;第二层具有短期记忆功能,在视觉信息不完整或机器人迷路时进行操作;第三层具有长期记忆和推理能力,监控机器人任务的完成情况,并安排不同任务的完成时间。视觉和运动系统以及其他监控单元被假设为有限状态自动机,控制体系结构基于这些自动机状态之间的转换。控制系统是灵活的,并且通过简单地引入新的状态可以很容易地获得新的功能。这种人工系统的智能行为主要是由记忆和创造简单而有用的世界表征的能力引起的。
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