基于黑板结构的多传感器数据溶合系统FS-1

本文借助于数据溶合方法中的引导法构成的系统在移动式机器人定位中取得了令人满意的结果.本系统的特点是:用分布式黑板作为计算机构,使系统具有并行处理能力;把时间(时序)推理引入系统.在数据溶合中考虑了时间的重要作用.本文提出的溶合方法和结构原则上可用于其它相关的问题领域.

一个用于自治智能移动式机器人导航和监控的实验系统

文中重点讨论了系统实现过程中,任务分解与行走命令下达,时序分配与同步,路标定位与行走误差修正.动态障碍感知,测定与响应和特别情况紧急处理等难题的解决策略及遇到的问题.

移动机器人环境建模的结构基自由网格法

本文给出的结构基自由网格法综合了正规栅格法和自由空间法的基本思想,依环境的结构信息确定地解决自由空间分割过程中构造想象边界的任意性问题,由此消除了路径的不确定性;此外,结构基自由网格模型可以在一定程度上消除规划路径“绕大弯”的现象。

基于人工势场方法的移动机器人模糊自校正系统

本文给出了移动机器人的虚力导航和运动规划系统。这种方法结合最小方差估计算法(LMSE)和模糊控制方法能有效地对机器人进行实时导航和避撞。在预测过程中,根据导航的不同阶段和预测误差的变化情况,采用Fuzzy规则动态地调整误差函数中的权重,使得预测过程尽可能准确。本文导航算法的基本思想是首先通过预测算法来获得移动机器人的运动信息,然后虚力系统根据预测信息决定机器人的将来的运动,仿真结果表明该方法实时性好,能准确躲避障碍物并且到达目标点。

轮式移动机器人沙地行驶控制建模与仿真研究

结合车轮沙土相互作用的力学分析,研究解决轮式移动机器人沙地行驶车轮过度滑转下陷问题。考虑纵列式重复通过车轮沙土力学参数的修正,建立六轮式沙地移动机器人的动力学模型,以车轮滑转率为状态变量,设计了移动机器人沙地行驶的滑模驱动控制器跟踪车轮期望滑转率。MATLAB/Simulink仿真结果表明,采用该控制器可以较快地跟踪期望滑转率,有效地限制机器人车轮的滑转,避免车轮的过度下陷。

Battling Reality

In the four years that the MIT Mobile Robot Project has benn in existence, we have built ten robots that focus research in various areas concerned with building intelligent systems. Towards this end, we have embarked on trying to build useful autonomous creatures that live and work in the real world. Many of the preconceived notions entertained before we started building our robots turned out to be misguided. Some issues we thought would be hard have worked successfully from day one and subsystems we imagined to be trivial have become tremendous time sinks. Oddly enough, one of our biggest failures has led to some of our favorite successes. This paper describes the changing paths our research has taken due to the lessons learned from the practical realities of building robots.

Specialization of Perceptual Processes

In this report, I discuss the use of vision to support concrete, everyday activity. I will argue that a variety of interesting tasks can be solved using simple and inexpensive vision systems. I will provide a number of working examples in the form of a state-of-the-art mobile robot, Polly, which uses vision to give primitive tours of the seventh floor of the MIT AI Laboratory. By current standards, the robot has a broad behavioral repertoire and is both simple and inexpensive (the complete robot was built for less than $20,000 using commercial board-level components). The approach I will use will be to treat the structure of the agent's activity---its task and environment---as positive resources for the vision system designer. By performing a careful analysis of task and environment, the designer can determine a broad space of mechanisms which can perform the desired activity. My principal thesis is that for a broad range of activities, the space of applicable mechanisms will be broad enough to include a number mechanisms which are simple and economical. The simplest mechanisms that solve a given problem will typically be quite specialized to that problem. One thus worries that building simple vision systems will be require a great deal of {it ad-hoc} engineering that cannot be transferred to other problems. My second thesis is that specialized systems can be analyzed and understood in a principled manner, one that allows general lessons to be extracted from specialized systems. I will present a general approach to analyzing specialization through the use of transformations that provably improve performance. By demonstrating a sequence of transformations that derive a specialized system from a more general one, we can summarize the specialization of the former in a compact form that makes explicit the additional assumptions that it makes about its environment. The summary can be used to predict the performance of the system in novel environments. Individual transformations can be recycled in the design of future systems.

Visual Navigation: Constructing and Utilizing Simple Maps of an Indoor Environment

The goal of this work is to navigate through an office environmentsusing only visual information gathered from four cameras placed onboard a mobile robot. The method is insensitive to physical changes within the room it is inspecting, such as moving objects. Forward and rotational motion vision are used to find doors and rooms, and these can be used to build topological maps. The map is built without the use of odometry or trajectory integration. The long term goal of the project described here is for the robot to build simple maps of its environment and to localize itself within this framework.

Evolving Controllers for Real Robots: A Survey of the Literature

Walker,J. and Garrett,S. and Wilson,M.S., 'Evolving Controllers for Real Robots: A Survey of the Literature', Adaptive Behavior, 2003, volume 11, number 3, pp 179--203, Sage

Fast line, arc/circle and leg detection from laser scan data in a player driver

A feature detection system has been developed for real-time identification of lines, circles and people legs from laser range data. A new method sutable for arc/circle detection is proposed: the Inscribed Angle Variance (IAV). Lines are detected using a recursive line fitting method.

Algoritmo neurogenético com vistas para o planejamento de rotas de robôs móveis autônomos

Pós-graduação em Ciência da Computação - IBILCE

Planeamento de rota em ambiente desconhecido

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

Perspectives and approaches for the internet of things

Dissertação para obtenção do Grau de Mestre em Engenharia Electrotécnica e de Computadores

A Colony Architecture for an Artificial Creature

This report describes a working autonomous mobile robot whose only goal is to collect and return empty soda cans. It operates in an unmodified office environment occupied by moving people. The robot is controlled by a collection of over 40 independent "behaviors'' distributed over a loosely coupled network of 24 processors. Together this ensemble helps the robot locate cans with its laser rangefinder, collect them with its on-board manipulator, and bring them home using a compass and an array of proximity sensors. We discuss the advantages of using such a multi-agent control system and show how to decompose the required tasks into component activities. We also examine the benefits and limitations of spatially local, stateless, and independent computation by the agents.

MARVEL: A System for Recognizing World Locations with Stereo Vision

To use a world model, a mobile robot must be able to determine its own position in the world. To support truly autonomous navigation, I present MARVEL, a system that builds and maintains its own models of world locations and uses these models to recognize its world position from stereo vision input. MARVEL is designed to be robust with respect to input errors and to respond to a gradually changing world by updating its world location models. I present results from real-world tests of the system that demonstrate its reliability. MARVEL fits into a world modeling system under development.