Development of ultra-small lightweight optical range sensor system

Abstract -We have developed a 2-D laser range sensor suitable for mobile robot platforms. The sensor features compactness, lightweight, high precision and low power consumption, and provides the wide scan angle with high resolution, which is very important for environment recognition by mobile robots. The basic technology for measuring the distance between the sensor and objects are; using amplitude modulation of light waves and detecting the phase difference between transmitted and the received one. This paper explains the specification of the proto-type sensor, the method of distance measurement and examples of experimental results

Multi-scale Point and Line Range Data Algorithms for Mapping and Localization

This paper presents a multi-scale point and line based representation of two-dimensional range scan data. The techniques are based on a multi-scale Hough transform and a tree representation of the environment’s features. The multiscale representation can lead to improved robustness and computational efficiencies in basic operations, such as matching and correspondence, that commonly arise in many localization and mapping procedures. For multi-scale matching and correspondence we introduce a χ^2 criterion that is calculated from the estimated variance in position of each detected line segment or point. This improved correspondence method can be used as the basis for simple scan-matching displacement estimation, as a part of a SLAM implementation, or as the basis for solutions to the kidnapped robot problem. Experimental results (using a Sick LMS-200 range scanner) show the effectiveness of our methods

Robotic riding mechanism for segway personal transporter.

Wong, Sheung Man.Thesis (M.Phil.)--Chinese University of Hong Kong, 2010.Includes bibliographical references (leaves 63-64).Abstracts in English and Chinese.Abstract --- p.i摘要 --- p.iiiAcknowledgements --- p.ivList of figures --- p.VChapter Chapter 1 --- Introduction --- p.1Chapter 1.1. --- Segway Personal Transporter (PT) --- p.1Chapter 1.2. --- Existing research using Segway Robotic Mobility Platform´ёØ (RMP) --- p.3Chapter 1.3. --- The ICSL Segway Rider --- p.9Chapter 1.4. --- Thesis outlines --- p.10Chapter Chapter 2 --- ICSL Segway Rider --- p.11Chapter 2.1. --- Design concept --- p.11Chapter 2.2. --- Design overview --- p.12Chapter 2.3. --- Actuating components --- p.14Chapter 2.4. --- Electronic and sensing components --- p.24Chapter 2.5. --- Software development of Segway Rider --- p.28Chapter 2.6. --- Chapter summary --- p.31Chapter Chapter 3 --- The grand challenge --- p.32Chapter 3.1. --- Objective --- p.32Chapter 3.2. --- Experiment --- p.33Chapter 3.3. --- Running lane tracking by computer vision --- p.34Chapter 3.3.1. --- Color space conversion --- p.36Chapter 3.3.2. --- Apply binary threshold --- p.37Chapter 3.3.3. --- Edge detection --- p.41Chapter 3.3.4. --- Hough transform --- p.46Chapter 3.3.5. --- Line analysis --- p.49Chapter 3.4. --- Chapter summary --- p.51Chapter Chapter 4 --- Stand and stay --- p.52Chapter 4.1. --- Introduction --- p.52Chapter 4.2. --- Box matching method --- p.53Chapter 4.3. --- Image processing steps --- p.55Chapter 4.4. --- Experiment --- p.58Chapter 4.5. --- Chapter summary --- p.60Chapter Chapter 5 --- Conclusion and future works --- p.61Chapter 5.1. --- Contributions --- p.61Chapter 5.2. --- Future works --- p.62Bibliography --- p.6

Basics search for simultaneous localization and mapping.

Tato práce se zabývá metodami simultánní lokalizace a mapování používanými v aplikacích mobilní robotiky ve světě. Cílem této práce je popsat existující a používané metody simultánní lokalizace a mapování. V první části je uvedeno rozdělení a popis jednotlivých podproblémů simultánní lokalizace a mapování. V druhé části jsou popsány konkrétní metody simultánní lokalizace a mapování. Třetí část se věnuje praktickým aplikacím metod simultánní lokalizace a mapování používaných v robotických úlohách ve světě. Poslední část je věnována robotickým aplikacím v rámci FSI VUT v Brně a použitelnosti jednotlivých metod pro tyto aplikace.This work deals with methods of simultaneous localization and mapping using in mobile robotic problems in the world. Main Goal of the work is describe existing and common using methods of simultaneous localization and mapping. The first part of the work deals with parting and description of each subproblems of simultaneous localization and mapping. The second part is note concrete methods of simultaneous localization and mapping. The third part is attending to practical application of simultaneous localization and mapping using in robotic tasks in the world. The last one is devoted to robotic application within the Faculty of Mechaniacal engineering at Brno Technical University and practicability apportionable methods for the applications.

Local Navigation of an Autonomous Mobile Robot

Cílem této diplomové práce je navrhnout koncept pro navigaci autonomního mobilního robota v parkovém prostředí. Konkrétně navrhnout metody lokalizace a detekce cesty s využitím dostupného senzorického systému, uvést matematický model pro fúzi těchto údajů a zvolenou vnitřní reprezentaci, a to s ohledem na budoucí plánovací a řídící algoritmy.This paper deals with the topic of design of a navigation system for an autonomous mobile robot in a park-like environment. Precisely, designing methods for road detection using available sensoric system, designing a mathematical model for fusion of these data, and suggesting a representation of an environment suitable for planning and local navigation.

Automatic Reconstruction of Textured 3D Models

Three dimensional modeling and visualization of environments is an increasingly important problem. This work addresses the problem of automatic 3D reconstruction and we present a system for unsupervised reconstruction of textured 3D models in the context of modeling indoor environments. We present solutions to all aspects of the modeling process and an integrated system for the automatic creation of large scale 3D models

A Multi-Resolution Pyramid for Outdoor Robot Terrain Perception

This paper addresses the problem of outdoor terrain modeling for the purposes of mobile robot navigation. We propose an approach in which a robot acquires a set of terrain models at differing resolutions. Our approach addresses one of the major shortcomings of Bayesian reasoning when applied to terrain modeling, namely artifacts that arise from the limited spatial resolution of robot perception. Limited spatial resolution causes small obstacles to be detectable only at close range. Hence, a Bayes filter estimating the state of terrain segments must consider the ranges at which that terrain is observed. We develop a multi-resolution approach that maintains multiple navigation maps, and derive rational arguments for the number of layers and their resolutions. We show that our approach yields significantly better results in a practical robot system, capable of acquiring detailed 3-D maps in large-scale outdoor environments