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Unformatted text preview: I Mobile Robots Navigation Mobile Robots Navigation Edited by Alejandra Barrera In-Tech intechweb.org Published by In-Teh
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© 2010 In-teh
Additional copies can be obtained from:
First published March 2010
Printed in India
Technical Editor: Goran Bajac
Cover designed by Dino Smrekar
Mobile Robots Navigation,
Edited by Alejandra Barrera p. cm.
ISBN 978-953-307-076-6 V Preface
Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining
and interpreting sensory information; (ii) exploration, as the strategy that guides the robot
to select the next direction to go; (iii) mapping, involving the construction of a spatial
representation by using the sensory information perceived; (iv) localization, as the strategy to
estimate the robot position within the spatial map; (v) path planning, as the strategy to find
a path towards a goal location being optimal or not; and (vi) path execution, where motor
actions are determined and adapted to environmental changes.
The book addresses those activities by integrating results from the research work of several
authors all over the world. Research cases are documented in 32 chapters organized within 7
categories next described.
The accurate perception of sensory information by the robot is critical to support the correct
construction of spatial representations to be exploited with navigational purposes. Different
types of sensor devices are introduced in this part of the book together with interpretation
methods of the acquired sensory information. Specifically, Chapter 1 presents the design of a
sensor combining omni-directional and stereoscopic vision to facilitate the 3D reconstruction
of the environment.
Chapter 2 describes the prototype of an optical azimuth angular sensor based on infrared
linear polarization to compute the robot’s position while navigating within an indoor arena.
Chapter 3 depicts the design of a stereoscopic vision module for a wheeled robot, where left
and right images from the same scene are captured, and one of two appearance-based pixel
descriptors for surface ground extraction are employed, luminance or Hue, depending on the
environment particular characteristics. This vision module also detects obstacle edges and
provides the reconstruction of the scene based on the stereo image analysis.
Chapter 4 presents a sensor setup for a 3D scanner to promote a fast 3D perception of those
regions in the robot’s vicinity that are relevant for collision avoidance. The acquired 3D data
is projected into the XY-plane in which the robot is moving and used to construct and update
egocentric 2.5D maps storing either the coordinates of closest obstacles or environmental
Closing this first part of the book, Chapter 5 depicts a sensor fusion technique where perceived
data are optimized and fully used to build navigation rules. VI Robot localization
In order to perform successful navigation through any given environment, robots need to
localize themselves within the corresponding spatial representation. A proper localization
allows the robot to exploit the map to plan a trajectory to navigate towards a goal destination.
In the second part of the book, four chapters address the problem of robot localization from
visual perception. In particular, Chapter 6 describes a localization algorithm using information
from a monocular camera and relying on separate estimations of rotation and translation to
provide an uncertainty feedback for both motion components while the robot navigates in
Chapter 7 proposes a self-localization method using a single visual image, where the
relationship between artificial or natural landmarks and known global reference points is
identified by a parallel projection model.
Chapter 8 presents computer simulations of robot heading and position estimation by using a
single vision sensor system to complement the encoders’ function during robot motion.
By means of experiments with a robotic wheelchair, Chapter 9 demonstrates the localization
ability within a topological map built by using only an omni-directional camera, where
environmental locations are recognized by identifying natural landmarks in the scene.
Several chapters focus on discussing path planning algorithms within static and dynamic
environments, and two of them deal with multiple robots. In this way, Chapter 10 presents a
path planning algorithm based on the use of a neural network to build up a collision penalty
function. Results from simulations show proper obstacle avoidance in both static and dynamic
Chapter 11 proposes a path planning algorithm avoiding obstacles by classifying them
according to their size to decide the next robot navigation action. The algorithm starts by
considering the shortest path, which is then expanded on either side spreading out by
considering the obstacles type and proximity.
In the context of indoor semi-structured environments full of corridors connecting offices and
laboratories, Chapter 12 compares several approaches developed for door identification based
on handle recognition, where doors are defined as goals for the robot during the path planning
process. The chapter describes a two-step multi-classifier that combines region detection and
feature extraction to increase the computational efficiency of the object recognition procedure.
In the context of planetary exploration vehicles, Chapter 13 describes a path planning and
navigation system based on the recognition of occluded areas in a local map. Experimental
results show the performance of a vehicle navigating through an irregular rocky terrain by
perceiving its environment, determining the next sensing position that maximizes the nonoccluded region within each local map, and executing the local path generated.
Chapter 14 presents a robotic architecture based on the integration of diverse computation
and communication processes to support the path planning and navigation of service robots.
Applied to the flock traffic navigation context, Chapter 15 introduces an algorithm capable of
planning paths for multiple agents on partially known and changing environments. VII Chapter 16 studies the problem of path planning and navigation of robot formations in static
environments, where a formation is defined, composed and repaired according to a proposed
One of the basic capabilities that mobile robots need to exhibit in navigating within any given
environment is obstacle detection and avoidance. This part of the book is dedicated to review
diverse mechanisms to deal with obstacles, being static and/or dynamic, implemented on
robots with different purposes, from service robots in domestic or office-like environments to
car-like vehicles in outdoors arenas. Specifically, Chapter 17 proposes an approach to reactive
obstacle avoidance for service robots by using the concept of artificial protection field, which
is understood as a dynamic geometrical neighborhood of the robot and a set of situation
assessment rules that determine if the robot needs to evade an object not present in its map
when its path was planned.
Chapter 18 describes a hierarchical action-control method for omni-directional mobile robots
to achieve a smooth obstacle avoidance ensuring safety in the presence of moving obstacles
Chapter 19 presents a contour-following controller to allow a wheeled robot to follow
discontinuous walls contours. This controller is integrated by a standard wall-following
controller and two complementary controllers to avoid collisions and find lost contours.
Chapter 20 introduces a fuzzy decision-making method to control the motion of car-like
vehicles in dynamic environments showing their ability to park in spatial configurations with
different placement of static obstacles, to run with the presence of dynamic obstacles, and to
achieve a final target from a given arbitrary initial position.
Chapter 21 presents a qualitative vision-based method to follow a path avoiding obstacles.
Analysis of navigational behavior
A correct evaluation of the navigational behavior of a mobile robotic system is required prior
its use solving real tasks in real-life scenarios. This part of the book stresses the importance
of employing qualitative and quantitative measures to analyze the robot performance. From
diverse perspectives, five chapters provide analysis metrics and/or results from comparative
analysis of existing methods to assess different behavioral aspects, from positioning
underwater vehicles to transmitting video signals from tele-operated robots.
From an information theory perspective, Chapter 22 studies the robot learning performance in
terms of the diversity of information available during training. Authors employ motivational
measures and entropy-based environmental measures to analyze the outcome of several
robotic navigation experiments.
Chapter 23 focuses on the study of positioning as a navigation problem where GPS reception
is limited or non-existent in the case of autonomous underwater vehicles that are forced to use
deadreckoning in between GPS sightings in order to navigate accurately. Authors provide
an analysis of different position estimators aiming at allowing vehicle designers to improve
performance and efficiency, as well as reduce vehicle instrumentation costs. VIII Chapter 24 provides results from analyzing several performance metrics to contrast mobile
robots navigation algorithms including safety, dimension and smoothness of the planned
Chapter 25 analyses the performance of different codecs in transmitting video signals from a
teleoperated mobile robot. Results are shown from robot tests in an indoor scenario.
With an aim at supporting educational and research activities, in Chapter 26, authors provide
a virtual environment to develop mobile robot systems including tools to simulate kinematics,
dynamics and control conditions, and monitor in real time the robot performance during
Inspiration from nature
Research cycles involving living organisms’ studies, computational modeling, and robotic
experimentation, have inspired for many years the understanding of the underlying
physiology and psychology of biological systems while also inspiring new robotic
architectures and applications. This part of the book describes two different studies that
have taken inspiration from nature to design and implement robotic systems exhibiting
navigational capabilities, from visual perception and map building to place recognition and
goal-directed behavior. Firstly, Chapter 27 presents a computational system-level model of rat
spatial cognition relating rat learning and memory processes by interaction of different brain
structures to endow a mobile robot with skills associated to global and relative positioning in
space, integration of the traveled path, use of kinesthetic and visual cues during orientation,
generation of topological-metric spatial representation of the unknown environment,
management of rewards, learning and unlearning of goal locations, navigation towards
the goal from any given departure location, and on-line adaptation of the cognitive map to
changes in the physical configuration of the environment. From a biological perspective, this
work aims at providing to neurobiologists/neuroethologists a technological platform to test
with robots biological experiments whose results can predict rodents’ spatial behavior.
Secondly, Chapter 28 proposes an approach inspired after developmental psychology and
some findings in neuroscience that allows a robot to use motor representations for learning
a complex task through imitation. This framework relies on development, understood as the
process where the robot acquires sophisticated capabilities over time as a sequence of simpler
learning steps. At the first level, the robot learns about sensory-motor coordination. Then,
motor actions are identified based on lower level, raw signals. Finally, these motor actions are
stored in a topological map and retrieved during navigation.
The book concludes by introducing different contexts and real scenarios where mobile robots
have been employed to solve diverse navigational tasks.
Presenting successful results along four testing years, Chapter 29 provides a mechatronic
description of an autonomous robot for agricultural tasks in greenhouses emphasizing the
use of specialized sensors during the development of control strategies of plants spraying
and robot navigation.
A sociological application is introduced in Chapter 30, consisting on providing electricpowered wheelchairs able to predict and avoid risky situations and navigate safely through
congested areas and confined spaces in the public transportation environment. Authors IX propose a high-level architecture that facilitates terrain surveillance and intelligence
gathering through laser sensors implanted in the wheelchair in order to anticipate accidents
by identifying obstacles and unusual patters of movement.
Chapter 31 describes the communication, sensory, and artificial intelligence systems
implemented on the CAESAR (Contractible Arms Elevating Search And Rescue) robot, which
supplies rescuers with critical information about the environment, such as gas detection,
before they enter and risk their lives in unstable conditions.
Finally, another monitoring system is depicted by Chapter 32. A mobile robot being
controlled by this system is able to perform a measuring task of physical variables, such as
high temperatures being potentially hazardous for humans, while navigating within a known
environment by following a predefined path.
The successful research cases included in this book demonstrate the progress of devices,
systems, models and architectures in supporting the navigational behavior of mobile robots
while performing tasks within several contexts. With no doubt, the overview of the state of
the art provided by the book may be a good starting point to acquire knowledge of intelligent
mobile robotics. Alejandra Barrera Mexico’s Autonomous Technological Institute (ITAM)
Mexico XI Contents
Preface 1. A 3D Omnidirectional Sensor For Mobile Robot Applications V
001 Rémi Boutteau, Xavier Savatier, Jean-Yves Ertaud and Bélahcène Mazari 2. Optical Azimuth Sensor for Indoor Mobile Robot Navigation 025 Keita Atsuumi and Manabu Sano 3. Vision Based Obstacle Detection Module for a Wheeled Mobile Robot 041 Oscar Montiel, Alfredo González and Roberto Sepúlveda 4. Fast 3D Perception for Collision Avoidance and SLAM in Domestic Environments 053 Dirk Holz, David Droeschel, Sven Behnke, Stefan May and Hartmut Surmann 5. Sensors Fusion Technique for Mobile Robot Navigation using Fuzzy Logic Control System 085 S.Parasuraman, Bijan Shirinzadeh and V.Ganapathy 6. Z∞ - Monocular Localization Algorithm with Uncertainty Analysis
for Outdoor Applications 107 Elmar Mair and Darius Burschka 7. Parallel Projection Based Self Localization Method for Mobile Navigation Applications 131 Shung Han Cho, Yuntai Kyong, Yunyoung Nam, Sangjin Hong and We-Duke Cho 8. Vision Based SLAM for Mobile Robot Navigation Using Distributed Filters 157 Young Jae Lee and Sankyung Sung 9. Omnidirectional vision based topological navigation 171 Toon Goedemé and Luc Van Gool 10. Neural Networks Based Navigation and Control of a Mobile Robot in a Partially Known Environment 197 Diana D. Tsankova 11. Navigation Planning with Human-Like Approach Yasar Ayaz, Atsushi Konno, Khalid Munawar, Teppei Tsujita and Masaru Uchiyama 223 XII 12. Approaches to door identification for robot navigation 241 E. Jauregi, E. Lazkano and B. Sierra 13. Path Planning and Execution for Planetary Exploration Rovers based on 3D Mapping 263 Andres Mora, Keiji Nagatani and Kazuya Yoshida 14. A Decentralised Software Process Approach For Real time Navigation of Service Robots 289 S. Veera Ragavan and Velappa Ganapathy 15. Multi-robot collective path finding in dynamic environments 307 Carlos Astengo-Noguez, Gildardo Sanchez-Ante, José Ramón Calzada and Ricardo Sisnett-Hernández 16. Navigation for mobile autonomous robots and their formations: An application of spatial reasoning induced from rough mereological geometry 329 Lech Polkowski and Pawel Osmialowski 17. An Artificial Protection Field Approach For Reactive Obstacle Avoidance in Mobile Robots 355 Victor Ayala-Ramirez, Jose A. Gasca-Martinez, Rigoberto Lopez-Padilla and Raul E. Sanchez-Yanez 18. Hierarchical action control technique based on prediction time for autonomous omni-directional mobile robots 367 Masaki Takahashi, Yoshimasa Tada, Takafumi Suzuki, and Kazuo Yoshida 19. Stable Switching Control of Wheeled Mobile Robots 379 Juan Marcos Toibero, Flavio Roberti, Fernando Auat Cheein, Carlos Soria and Ricardo Carelli 20. PFC Fuzzy Decision-Making Control and Its Application to Car-Like Mobile Vehicle 401 You-gen Chen, Seiji Yasunobu,Wei-hua Gui, Ren-yong Wei and Zhi-yong Li 21. Vision-Based Path Following Without Calibration 427 Zhichao Chen and Stanley T. Birchfield 22. Motivation and Local Image Entropy Based Measures in Evolutionary Mobile Robot Navigation 447 Tomás Arredondo and Wolfgang Freund 23. 6-DoF Navigation Systems for Autonomous Underwater Vehicles 457 Andrew Lammas, Karl Sammut and Fangpo He 24. Quantitative Performance Metrics for Mobile Robots Navigation Nelson David Muñoz Ceballos, Jaime Alejandro Valencia and Nelson Londoño Ospina 485 XIII 25. Testing performance of current video codecs in teleoperated mobile robot applications: a practical experience 501 Pablo Piñol, Otoniel López, Miguel Martínez-Rach, M.P. Malumbres, José Oliver and Carlos Calafate 26. Virtual Simulator for Design of Mobile Robot Control and Navigation Systems 515 Leonimer F Melo , Jose F Mangili Jr, Fernando C Dias Neto and Joao M Rosario 27. Robot Topological Mapping and Goal-Oriented Navigation Based on Rat Spatial Cognition 535 Alejandra Barrera 28. Topological Mapping and Navigation using a Developmental Learning Approach based on Imitation through Sensory-motor Maps 563 Raquel Frizera Vassallo, Hans Jörg Andreas Schneebeli and José Santos-Victor 29. A mechatronic description of an autonomous mobile robot for agricultural tasks in greenhouses 583 Julián Sánchez-Hermosilla, Francisco Rodríguez, Ramón González, José Luís Guzmán and Manuel Berenguel 30. A Mechatronics Vision for Smart Wheelchairs 609 Yoshiyuki Noda, Akira Kawaguchi and Kazuhiko Terashima 31. Communication and Artificial Intelligence systems used for the CAESAR robot 629 Riaan Stopforth (ZS5RSA), Glen Bright and R. Harley 32. Intelligent Control and Sensor Fusion of a Mobile Robot Based Monitoring System Benítez-Read, Jorge S. and Rojas-Ramírez, Erick 655 A 3D Omnidirectional Sensor For Mobile Robot Applications 1 X1
A 3D Omnidirectional Sensor
For Mobile Robot Applications
Rémi Boutteau, Xavier Savatier, Jean-Yves Ertaud and Bélahcène Mazari Institut de Recherche en Systèmes Electroniques Embarqués (IRSEEM)
France 1. Introduction
In most of the missions a mobile robot has to achieve – intervention in hostile environments...
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- SLAM, Alejandra Barrera