Cinematica dei Robot Mobili su Ruote. Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo
|
|
- Phillip Cameron
- 5 years ago
- Views:
Transcription
1 Cinematica dei Robot Mobili su Ruote Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo
2 Riferimenti bibliografici Roland SIEGWART, Illah R. NOURBAKHSH Introduction to Autonomous Mobile Robots Capitolo 2.3 «Wheeled Mobile Robots» 2
3 Wheeled Mobile Robots (WMR) 3
4 Wheeled Mobile Robots (WMR) ocomotion the process of causing an robot to move. In order to produce motion, forces must be applied to the robot Motor output, payload Kinematics study of the mathematics of motion without considering the forces that affect the motion. Deals with the geometric relationships that govern the system Deals with the relationship between control parameters and the behavior of a system. Dynamics study of motion in which these forces are modeled Deals with the relationship between force and motions. 4
5 Mobile Robot Kinematics Description of mechanical behavior of the robot for design and control Mobile robots can move unbound with respect to its environment there is no direct way to measure the robot s position Position must be integrated over time eads to inaccuracies of the position (motion) estimate the number 1 challenge in mobile robotics Understanding mobile robot motion starts with understanding wheel constraints placed on the robots mobility 5
6 Wheels Rolling motion ateral slip 6
7 Idealized Rolling Wheel Non-slipping and pure rolling Assumptions 1. The robot is built from rigid mechanisms. 2. No slip occurs in the orthogonal direction of rolling (nonslipping). 3. No translational slip occurs between the wheel and the floor (pure rolling). 4. The robot contains at most one steering lin per wheel. 5. All steering axes are perpendicular to the floor. 7
8 Robot wheel parameters For low velocities, rolling is a reasonable wheel model. This is the model that will be considered in the inematics models of wheeled mobile robots (WMR) Wheel parameters: r = wheel radius v = wheel linear velocity w = wheel angular velocity t = steering velocity 8
9 Wheel Types Fixed wheel Centered orientable wheel Off-centered orientable wheel (Castor wheel) Swedish wheel:omnidirectional property 9
10 Examples of WMR Smooth motion Ris of slipping Some times use roller-ball to mae balance Bi-wheel type robot Caterpillar type robot Exact straight motion Robust to slipping Inexact modeling of turning Free motion Complex structure Weaness of the frame Omnidirectional robot 10
11 Mobile Robot ocomotion Instantaneous center of rotation (ICR) or Instantaneous center of curvature (ICC) A cross point of all axes of the wheels 11
12 Non-holonomic constraint A non-holonomic constraint is a constraint on the feasible velocities of a body So what does that mean? Your robot can move in some directions (forward and bacward), but not others (sideward). The robot can instantly move forward and bacward, but can not move sideward Parallel paring, Series of maneuvers 12
13 Differential Drive Relazione tra le velocità delle ruote (V e V R ) e la velocità del robot (TWIST) V Control input Twist { v : inear velocity of the robot : Angular velocity of the robot R = curvature radius V = R * 13
14 Differential Drive V ( R ) 2 V R ( R ) 2 V 14
15 Differential Drive V Straight motion R = Infinity VR = V Rotational motion R = 0 VR = -V 15
16 Differential Drive V V Twist { Velocità ruote { 16
17 Tricycle Three wheels and odometers on the two rear wheels Steering and power are provided through the front wheel control variables: steering direction α(t) angular velocity of steering wheel w s (t) The ICC must lie on the line that passes through, and is perpendicular to, the fixed rear wheels 17
18 Tricycle inear velocity of steering wheel 18
19 Tricycle Kinematics model in the world frame ---Posture inematics model 19
20 Car Drive (Acerman Steering) 20 R Used in motor vehicles, the inside front wheel is rotated slightly sharper than the outside wheel (reduces tire slippage). Acerman steering provides a fairly accurate dead-reconing solution while supporting traction and ground clearance. Generally the method of choice for outdoor autonomous vehicles. where d = lateral wheel separation l = longitudinal wheel separation i = relative steering angle of inside wheel o = relative steering angle of outside wheel R=distance between ICC to centerline of the vehicle
21 Carrello 21
22 Synchronous Drive In a synchronous drive robot (synchronous drive) each wheel is capable of being driven and steered. 22
23 Synchronous Drive All the wheels turn in unison All of the three wheels point in the same direction and turn at the same rate This is typically achieved through the use of a complex collection of belts that physically lin the wheels together Two independent motors, one rolls all wheels forward, one rotate them for turning The vehicle controls the direction in which the wheels point and the rate at which they roll Because all the wheels remain parallel the synchro drive always rotate about the center of the robot The synchro drive robot has the ability to control the orientation θ of their pose directly. 23
24 Omidirectional 24 Swedish Wheel
25 Odometry for Differential Drive Rovers
26 Differential Drive V Straight motion R = Infinity VR = V Rotational motion R = 0 VR = -V 26
27 Basic Motion Control Velocity Profile : Radius of rotation : ength of path : Angle of rotation
28 Differential Drive: odometria y dd 1 2 r R t t dt y θ x x r t t t 1 t r t t cos t 2 R R dt dt dd x 28 y 1 t r t t sin t 2 R dt
29 Differential Drive: odometria Esempio : velocità costanti R R t t t r t R t r t x R R R sin 2 t r t y R R R cos 2 29
30 Differential Drive: odometria D DR R r r t t t t 1 1 Distanze percorse dalle due ruote nell intervallo di tempo t t -1 r 2 DR DR D D Raggio di curvatura del robot nell intervallo di tempo t t -1 x y x y 1 DR D r sin 1 1 r cos 1 1 sin cos Posizione del robot all istante t 30
31 Effector Noise: Odometry, Dead Reconing Odometry and dead reconing: Position update is based on proprioceptive sensors Odometry: wheel sensors only Dead reconing: also heading sensors The movement of the robot, sensed with wheel encoders and/or heading sensors is integrated to the position. Pros: Straight forward, easy Cons: Errors are integrated -> unbound Using additional heading sensors (e.g. gyroscope) might help to reduce the cumulated errors, but the main problems remain the same. 31
32 Imprecisione dell odometria Nr. posizionamenti = 35 ; Dati di scostamento : Media = 11 gradi ; Deviazione standard = 5.47 gradi 32
33 Odometry: Error sources deterministic (systematic) non-deterministic (non-systematic) deterministic errors can be eliminated by proper calibration of the system. non-deterministic errors have to be described by error models and will always leading to uncertain position estimate. Major Error Sources: imited resolution during integration (time increments, measurement resolution ) Misalignment of the wheels (deterministic) Unequal wheel diameter (deterministic) Variation in the contact point of the wheel Unequal floor contact (slipping, not planar ) 33
34 Odometry: Classification of Integration Errors Range error: integrated path length (distance) of the robots movement sum of the wheel movements Turn error: similar to range error, but for turns difference of the wheel motions Drift error: difference in the error of the wheels leads to an error in the robots angular orientation Over long periods of time, turn and drift errors far outweigh range errors! Consider moving forward on a straight line along the x axis. The error in the y- position introduced by a move of d meters will have a component of dsind, which can be quite large as the angular error D grows. 34
35 Differential Drive: odometria D DR R r r t t t 1 t 1 r 2 DR DR D D x y x y 1 DR D r sin 1 1 r cos 1 1 sin cos Posizione del robot all istante t 35
36 Odometry: Growth of Pose uncertainty for Straight ine Movement Note: Errors perpendicular to the direction of movement are growing much faster! 36
37 Odometry: Growth of Pose uncertainty for Movement on a Circle Note: Errors ellipse does not remain perpendicular to the direction of movement! 37
38 Riduzione degli errori non sistematici Utilizzo di ruote ausiliarie non motrici 38
Localization, Where am I?
5.1 Localization, Where am I?? position Position Update (Estimation?) Encoder Prediction of Position (e.g. odometry) YES matched observations Map data base predicted position Matching Odometry, Dead Reckoning
More information10/11/07 1. Motion Control (wheeled robots) Representing Robot Position ( ) ( ) [ ] T
3 3 Motion Control (wheeled robots) Introduction: Mobile Robot Kinematics Requirements for Motion Control Kinematic / dynamic model of the robot Model of the interaction between the wheel and the ground
More informationCMPUT 412 Motion Control Wheeled robots. Csaba Szepesvári University of Alberta
CMPUT 412 Motion Control Wheeled robots Csaba Szepesvári University of Alberta 1 Motion Control (wheeled robots) Requirements Kinematic/dynamic model of the robot Model of the interaction between the wheel
More informationMotion Control (wheeled robots)
Motion Control (wheeled robots) Requirements for Motion Control Kinematic / dynamic model of the robot Model of the interaction between the wheel and the ground Definition of required motion -> speed control,
More informationMobile Robot Kinematics
Mobile Robot Kinematics Dr. Kurtuluş Erinç Akdoğan kurtuluserinc@cankaya.edu.tr INTRODUCTION Kinematics is the most basic study of how mechanical systems behave required to design to control Manipulator
More informationLecture 1 Wheeled Mobile Robots (WMRs)
Lecture 1 Wheeled Mobile Robots (WMRs) Course Chair: Prof. M. De Cecco Teaching: A. Cesarini Mechatronics Department, University of Trento Email: andrea.cesarini@unitn.it http://www.miro.ing.unitn.it/
More informationLocalization and Map Building
Localization and Map Building Noise and aliasing; odometric position estimation To localize or not to localize Belief representation Map representation Probabilistic map-based localization Other examples
More informationMobile Robotics. Marcello Restelli. Dipartimento di Elettronica e Informazione Politecnico di Milano tel:
Marcello Restelli Dipartimento di Elettronica e Informazione Politecnico di Milano email: restelli@elet.polimi.it tel: 02-2399-3470 Mobile Robotics Robotica for Computer Engineering students A.A. 2006/2007
More informationMEM380 Applied Autonomous Robots Winter Robot Kinematics
MEM38 Applied Autonomous obots Winter obot Kinematics Coordinate Transformations Motivation Ultimatel, we are interested in the motion of the robot with respect to a global or inertial navigation frame
More informationUnit 2: Locomotion Kinematics of Wheeled Robots: Part 3
Unit 2: Locomotion Kinematics of Wheeled Robots: Part 3 Computer Science 4766/6778 Department of Computer Science Memorial University of Newfoundland January 28, 2014 COMP 4766/6778 (MUN) Kinematics of
More informationRobotics (Kinematics) Winter 1393 Bonab University
Robotics () Winter 1393 Bonab University : most basic study of how mechanical systems behave Introduction Need to understand the mechanical behavior for: Design Control Both: Manipulators, Mobile Robots
More informationEncoder applications. I Most common use case: Combination with motors
3.5 Rotation / Motion - Encoder applications 64-424 Intelligent Robotics Encoder applications I Most common use case: Combination with motors I Used to measure relative rotation angle, rotational direction
More informationEE565:Mobile Robotics Lecture 2
EE565:Mobile Robotics Lecture 2 Welcome Dr. Ing. Ahmad Kamal Nasir Organization Lab Course Lab grading policy (40%) Attendance = 10 % In-Lab tasks = 30 % Lab assignment + viva = 60 % Make a group Either
More informationFundamental problems in mobile robotics
ROBOTICS 01PEEQW Basilio Bona DAUIN Politecnico di Torino Mobile & Service Robotics Kinematics Fundamental problems in mobile robotics Locomotion: how the robot moves in the environment Perception: how
More informationCHAPTER 3 MATHEMATICAL MODEL
38 CHAPTER 3 MATHEMATICAL MODEL 3.1 KINEMATIC MODEL 3.1.1 Introduction The kinematic model of a mobile robot, represented by a set of equations, allows estimation of the robot s evolution on its trajectory,
More informationBEST2015 Autonomous Mobile Robots Lecture 2: Mobile Robot Kinematics and Control
BEST2015 Autonomous Mobile Robots Lecture 2: Mobile Robot Kinematics and Control Renaud Ronsse renaud.ronsse@uclouvain.be École polytechnique de Louvain, UCLouvain July 2015 1 Introduction Mobile robot
More informationMobile Robots Locomotion
Mobile Robots Locomotion Institute for Software Technology 1 Course Outline 1. Introduction to Mobile Robots 2. Locomotion 3. Sensors 4. Localization 5. Environment Modelling 6. Reactive Navigation 2 Today
More information1 Differential Drive Kinematics
CS W4733 NOTES - Differential Drive Robots Note: these notes were compiled from Dudek and Jenkin, Computational Principles of Mobile Robotics. 1 Differential Drive Kinematics Many mobile robots use a drive
More informationIntroduction to Robotics
Introduction to Robotics Ph.D. Antonio Marin-Hernandez Artificial Intelligence Department Universidad Veracruzana Sebastian Camacho # 5 Xalapa, Veracruz Robotics Action and Perception LAAS-CNRS 7, av du
More informationChapter 4 Dynamics. Part Constrained Kinematics and Dynamics. Mobile Robotics - Prof Alonzo Kelly, CMU RI
Chapter 4 Dynamics Part 2 4.3 Constrained Kinematics and Dynamics 1 Outline 4.3 Constrained Kinematics and Dynamics 4.3.1 Constraints of Disallowed Direction 4.3.2 Constraints of Rolling without Slipping
More informationLocalization and Map Building
Localization and Map Building Noise and aliasing; odometric position estimation To localize or not to localize Belief representation Map representation Probabilistic map-based localization Other examples
More informationKinematics, Kinematics Chains CS 685
Kinematics, Kinematics Chains CS 685 Previously Representation of rigid body motion Two different interpretations - as transformations between different coord. frames - as operators acting on a rigid body
More informationDEAD RECKONING FOR MOBILE ROBOTS USING TWO OPTICAL MICE
DEAD RECKONING FOR MOBILE ROBOTS USING TWO OPTICAL MICE Andrea Bonarini Matteo Matteucci Marcello Restelli Department of Electronics and Information Politecnico di Milano Piazza Leonardo da Vinci, I-20133,
More informationExam in DD2426 Robotics and Autonomous Systems
Exam in DD2426 Robotics and Autonomous Systems Lecturer: Patric Jensfelt KTH, March 16, 2010, 9-12 No aids are allowed on the exam, i.e. no notes, no books, no calculators, etc. You need a minimum of 20
More informationCS283: Robotics Fall 2016: Sensors
CS283: Robotics Fall 2016: Sensors Sören Schwertfeger / 师泽仁 ShanghaiTech University Robotics ShanghaiTech University - SIST - 23.09.2016 2 REVIEW TRANSFORMS Robotics ShanghaiTech University - SIST - 23.09.2016
More informationMotion Planning 2D. Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo
Motion Planning 2D Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo Tratto dai corsi: CS 326A: Motion Planning ai.stanford.edu/~latombe/cs326/2007/index.htm Prof. J.C. Latombe Stanford
More informationIntroduction to Autonomous Mobile Robots
Introduction to Autonomous Mobile Robots second edition Roland Siegwart, Illah R. Nourbakhsh, and Davide Scaramuzza The MIT Press Cambridge, Massachusetts London, England Contents Acknowledgments xiii
More informationCentre for Autonomous Systems
Robot Henrik I Centre for Autonomous Systems Kungl Tekniska Högskolan hic@kth.se 27th April 2005 Outline 1 duction 2 Kinematic and Constraints 3 Mobile Robot 4 Mobile Robot 5 Beyond Basic 6 Kinematic 7
More informationIntroduction to Information Science and Technology (IST) Part IV: Intelligent Machines and Robotics Planning
Introduction to Information Science and Technology (IST) Part IV: Intelligent Machines and Robotics Planning Sören Schwertfeger / 师泽仁 ShanghaiTech University ShanghaiTech University - SIST - 10.05.2017
More informationIntroduction to Mobile Robotics Probabilistic Motion Models
Introduction to Mobile Robotics Probabilistic Motion Models Wolfram Burgard, Michael Ruhnke, Bastian Steder 1 Robot Motion Robot motion is inherently uncertain. How can we model this uncertainty? Dynamic
More informationKinematics of Wheeled Robots
CSE 390/MEAM 40 Kinematics of Wheeled Robots Professor Vijay Kumar Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania September 16, 006 1 Introduction In this chapter,
More informationRobotics and Autonomous Systems
Robotics and Autonomous Systems Lecture 6: Perception/Odometry Terry Payne Department of Computer Science University of Liverpool 1 / 47 Today We ll talk about perception and motor control. 2 / 47 Perception
More informationRobotics and Autonomous Systems
Robotics and Autonomous Systems Lecture 6: Perception/Odometry Simon Parsons Department of Computer Science University of Liverpool 1 / 47 Today We ll talk about perception and motor control. 2 / 47 Perception
More informationZürich. Roland Siegwart Margarita Chli Martin Rufli Davide Scaramuzza. ETH Master Course: L Autonomous Mobile Robots Summary
Roland Siegwart Margarita Chli Martin Rufli Davide Scaramuzza ETH Master Course: 151-0854-00L Autonomous Mobile Robots Summary 2 Lecture Overview Mobile Robot Control Scheme knowledge, data base mission
More informationPractical Robotics (PRAC)
Practical Robotics (PRAC) A Mobile Robot Navigation System (1) - Sensor and Kinematic Modelling Nick Pears University of York, Department of Computer Science December 17, 2014 nep (UoY CS) PRAC Practical
More informationIntroduction to Mobile Robotics
Introduction to Mobile Robotics Olivier Aycard Associate Professor University of Grenoble Laboratoire d Informatique de Grenoble http://membres-liglab.imag.fr/aycard olivier. 1/22 What is a robot? Robot
More informationROBOTICS AND AUTONOMOUS SYSTEMS
ROBOTICS AND AUTONOMOUS SYSTEMS Simon Parsons Department of Computer Science University of Liverpool LECTURE 6 PERCEPTION/ODOMETRY comp329-2013-parsons-lect06 2/43 Today We ll talk about perception and
More informationMOBILE ROBOTIC SYSTEM FOR GROUND-TESTING OF MULTI-SPACECRAFT PROXIMITY OPERATIONS
MOBILE ROBOTIC SYSTEM FOR GROUND-TESTING OF MULTI-SPACECRAFT PROXIMITY OPERATIONS INTRODUCTION James Doebbler, Jeremy Davis, John Valasek, John Junkins Texas A&M University, College Station, TX 77843 Ground
More informationForward kinematics and Denavit Hartenburg convention
Forward kinematics and Denavit Hartenburg convention Prof. Enver Tatlicioglu Department of Electrical & Electronics Engineering Izmir Institute of Technology Chapter 5 Dr. Tatlicioglu (EEE@IYTE) EE463
More informationChapter 2 Intelligent Behaviour Modelling and Control for Mobile Manipulators
Chapter Intelligent Behaviour Modelling and Control for Mobile Manipulators Ayssam Elkady, Mohammed Mohammed, Eslam Gebriel, and Tarek Sobh Abstract In the last several years, mobile manipulators have
More informationIntroduction to Mobile Robotics
Introduction to Mobile Robotics Olivier Aycard Associate Professor University of Grenoble Laboratoire d Informatique de Grenoble http://membres-liglab.imag.fr/aycard 1/29 Some examples of mobile robots
More informationImproving autonomous orchard vehicle trajectory tracking performance via slippage compensation
Improving autonomous orchard vehicle trajectory tracking performance via slippage compensation Dr. Gokhan BAYAR Mechanical Engineering Department of Bulent Ecevit University Zonguldak, Turkey This study
More informationLocalization, Mapping and Exploration with Multiple Robots. Dr. Daisy Tang
Localization, Mapping and Exploration with Multiple Robots Dr. Daisy Tang Two Presentations A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping, by Thrun, Burgard
More informationRobotics. Lecture 5: Monte Carlo Localisation. See course website for up to date information.
Robotics Lecture 5: Monte Carlo Localisation See course website http://www.doc.ic.ac.uk/~ajd/robotics/ for up to date information. Andrew Davison Department of Computing Imperial College London Review:
More informationChapter 4: Kinematics of Rigid Bodies
Chapter 4: Kinematics of Rigid Bodies Advanced Dynamics Lecturer: Hossein Nejat Fall 2016 A rigid body is defined to be a collection of particles whose distance of separation is invariant. In this circumstance,
More informationOmni-Directional Mobility Using Active Split Offset Castors
Haoyong Yu Matthew Spenko Steven Dubowsky Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139 e-mail: dubowsky@mit.edu Omni-Directional Mobility Using Active
More informationSensor Modalities. Sensor modality: Different modalities:
Sensor Modalities Sensor modality: Sensors which measure same form of energy and process it in similar ways Modality refers to the raw input used by the sensors Different modalities: Sound Pressure Temperature
More informationMotion Models (cont) 1 3/15/2018
Motion Models (cont) 1 3/15/018 Computing the Density to compute,, and use the appropriate probability density function; i.e., for zeromean Gaussian noise: 3/15/018 Sampling from the Velocity Motion Model
More informationDYNAMIC POSITIONING OF A MOBILE ROBOT USING A LASER-BASED GONIOMETER. Joaquim A. Batlle*, Josep Maria Font*, Josep Escoda**
DYNAMIC POSITIONING OF A MOBILE ROBOT USING A LASER-BASED GONIOMETER Joaquim A. Batlle*, Josep Maria Font*, Josep Escoda** * Department of Mechanical Engineering Technical University of Catalonia (UPC)
More informationMobile Robotics. Mathematics, Models, and Methods. HI Cambridge. Alonzo Kelly. Carnegie Mellon University UNIVERSITY PRESS
Mobile Robotics Mathematics, Models, and Methods Alonzo Kelly Carnegie Mellon University HI Cambridge UNIVERSITY PRESS Contents Preface page xiii 1 Introduction 1 1.1 Applications of Mobile Robots 2 1.2
More informationLecture «Robot Dynamics»: Multi-body Kinematics
Lecture «Robot Dynamics»: Multi-body Kinematics 151-0851-00 V lecture: CAB G11 Tuesday 10:15 12:00, every week exercise: HG E1.2 Wednesday 8:15 10:00, according to schedule (about every 2nd week) Marco
More informationLecture «Robot Dynamics»: Kinematics 3
Lecture «Robot Dynamics»: Kinematics 3 151-0851-00 V lecture: CAB G11 Tuesday 10:15 12:00, every week exercise: HG E1.2 Wednesday 8:15 10:00, according to schedule (about every 2nd week) Marco Hutter,
More informationSimultaneous Localization and Mapping (SLAM)
Simultaneous Localization and Mapping (SLAM) RSS Lecture 16 April 8, 2013 Prof. Teller Text: Siegwart and Nourbakhsh S. 5.8 SLAM Problem Statement Inputs: No external coordinate reference Time series of
More informationProject 1 : Dead Reckoning and Tracking
CS3630 Spring 2012 Project 1 : Dead Reckoning and Tracking Group : Wayward Sons Sameer Ansari, David Bernal, Tommy Kazenstein 2/8/2012 Wayward Sons CS3630 Spring 12 Project 1 Page 2 of 12 CS 3630 (Spring
More informationFinal Exam Practice Fall Semester, 2012
COS 495 - Autonomous Robot Navigation Final Exam Practice Fall Semester, 2012 Duration: Total Marks: 70 Closed Book 2 hours Start Time: End Time: By signing this exam, I agree to the honor code Name: Signature:
More informationEE565:Mobile Robotics Lecture 3
EE565:Mobile Robotics Lecture 3 Welcome Dr. Ahmad Kamal Nasir Today s Objectives Motion Models Velocity based model (Dead-Reckoning) Odometry based model (Wheel Encoders) Sensor Models Beam model of range
More informationKinematic Modelling of Tracked Vehicles by Experimental Identification
Kinematic Modelling of Tracked Vehicles by Experimental Identification J.L. Martínez, A. Mandow, J. Morales, A. García-Cerezo and S. Pedraza Dpto. Ingeniería de Sistemas y Automática. Universidad de Málaga
More informationDETC THREE-DIMENSIONAL KINEMATIC ANALYSIS OF THE ACTUATED SPOKE WHEEL ROBOT. September 10-13, 2006, Philadelphia, Pennsylvania, USA
Proceedings Proceedings of IDETC/CIE of IDETC 06 2006 ASME 2006 ASME International International Design Design Engineering Engineering Technical Technical Conferences Conferences & September Computers
More informationLecture «Robot Dynamics»: Kinematics 3
Lecture «Robot Dynamics»: Kinematics 3 151-0851-00 V lecture: CAB G11 Tuesday 10:15 12:00, every week exercise: HG E1.2 Wednesday 8:15 10:00, according to schedule (about every 2nd week) office hour: LEE
More informationS-SHAPED ONE TRAIL PARALLEL PARKING OF A CAR-LIKE MOBILE ROBOT
S-SHAPED ONE TRAIL PARALLEL PARKING OF A CAR-LIKE MOBILE ROBOT 1 SOE YU MAUNG MAUNG, 2 NU NU WIN, 3 MYINT HTAY 1,2,3 Mechatronic Engineering Department, Mandalay Technological University, The Republic
More informationFACOLTÀ DI INGEGNERIA DELL INFORMAZIONE ELECTIVE IN ROBOTICS. Quadrotor. Motion Planning Algorithms. Academic Year
FACOLTÀ DI INGEGNERIA DELL INFORMAZIONE ELECTIVE IN ROBOTICS Quadrotor Motion Planning Algorithms Prof. Marilena Vendittelli Prof. Jean-Paul Laumond Jacopo Capolicchio Riccardo Spica Academic Year 2010-2011
More informationThis was written by a designer of inertial guidance machines, & is correct. **********************************************************************
EXPLANATORY NOTES ON THE SIMPLE INERTIAL NAVIGATION MACHINE How does the missile know where it is at all times? It knows this because it knows where it isn't. By subtracting where it is from where it isn't
More informationAutonomous Mobile Robots Using Real Time Kinematic Signal Correction and Global Positioning System Control
Paper 087, IT 304 Autonomous Mobile Robots Using Real Time Kinematic Signal Correction and Global Positioning System Control Thongchai Phairoh, Keith Williamson Virginia State University tphairoh@vsu.edu
More informationSimultaneous Localization
Simultaneous Localization and Mapping (SLAM) RSS Technical Lecture 16 April 9, 2012 Prof. Teller Text: Siegwart and Nourbakhsh S. 5.8 Navigation Overview Where am I? Where am I going? Localization Assumed
More informationMotion Planning: Probabilistic Roadmaps. Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo
Motion Planning: Probabilistic Roadmaps Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo Tratto dalla lezione: Basic Motion Planning for a Point Robot CS 326A: Motion Planning ai.stanford.edu/~latombe/cs326/2007/index.htm
More informationAn Experimental Exploration of Low-Cost Solutions for Precision Ground Vehicle Navigation
An Experimental Exploration of Low-Cost Solutions for Precision Ground Vehicle Navigation Daniel Cody Salmon David M. Bevly Auburn University GPS and Vehicle Dynamics Laboratory 1 Introduction Motivation
More informationA Simplified Vehicle and Driver Model for Vehicle Systems Development
A Simplified Vehicle and Driver Model for Vehicle Systems Development Martin Bayliss Cranfield University School of Engineering Bedfordshire MK43 0AL UK Abstract For the purposes of vehicle systems controller
More informationSimulation and mathematical modeling of Automatic Control of Wheeled Mobile Robots
Simulation and mathematical modeling of Automatic Control of Wheeled Mobile Robots Six-months practical training report Submitted in partial fulfillment of the requirement for the award of the degree of
More informationA General Framework for Mobile Robot Pose Tracking and Multi Sensors Self-Calibration
A General Framework for Mobile Robot Pose Tracking and Multi Sensors Self-Calibration Davide Cucci, Matteo Matteucci {cucci, matteucci}@elet.polimi.it Dipartimento di Elettronica, Informazione e Bioingegneria,
More informationStraight Line motion with rigid sets
Straight ine motion with rigid sets arxiv:40.4743v [math.mg] 9 Jan 04 Robert Connelly and uis Montejano January 7, 08 Abstract If one is given a rigid triangle in the plane or space, we show that the only
More informationCS283: Robotics Fall 2017: Kinematics
CS283: Robotics Fall 2017: Kinematics Andre Rosendo ShanghaiTech University Robotics ShanghaiTech University - SIST - 25.09.2016 2 Messages Publisher does not know about subscribers Subscribers do not
More informationOmnidirectional Drive Systems Kinematics and Control
Omnidirectional Drive Systems Kinematics and Control Presented by: Andy Baker President, AndyMark, Inc., FRC 45 Ian Mackenzie Master s Student, Univ. of Waterloo, FRC 1114 2008 FIRST Robotics Conference
More informationCS283: Robotics Fall 2016: Kinematics
CS283: Robotics Fall 2016: Kinematics Sören Schwertfeger / 师泽仁 ShanghaiTech University Robotics ShanghaiTech University - SIST - 21.09.2016 2 Messages Publisher does not know about subscribers Subscribers
More informationHolonomic Omni-Directional Vehicle with New Omni-Wheel Mechanism
Proceedings of the 2001 EEE nternational Conference on Robotics 8 Automation Seoul, Korea. May 21-26, 2001 Holonomic Omni-Directional Vehicle with New Omni-Wheel Mechanism Riichiro DAMOTO, Wendy CHENG
More informationINDOOR AND OUTDOOR LOCALIZATION OF A MOBILE ROBOT FUSING SENSOR DATA. A Thesis Presented. Md Maruf Ibne Hasan
INDOOR AND OUTDOOR LOCALIZATION OF A MOBILE ROBOT FUSING SENSOR DATA A Thesis Presented By Md Maruf Ibne Hasan to The Department of Electrical and Computer Engineering in partial fulfillment of the requirements
More informationWEEKS 1-2 MECHANISMS
References WEEKS 1-2 MECHANISMS (METU, Department of Mechanical Engineering) Text Book: Mechanisms Web Page: http://www.me.metu.edu.tr/people/eres/me301/in dex.ht Analitik Çözümlü Örneklerle Mekanizma
More informationEvaluating the Performance of a Vehicle Pose Measurement System
Evaluating the Performance of a Vehicle Pose Measurement System Harry Scott Sandor Szabo National Institute of Standards and Technology Abstract A method is presented for evaluating the performance of
More informationNon-holonomic Planning
Non-holonomic Planning Jane Li Assistant Professor Mechanical Engineering & Robotics Engineering http://users.wpi.edu/~zli11 Recap We have learned about RRTs. q new q init q near q rand But the standard
More informationAnalysis and Experimental Kinematics of a Skid-Steering Wheeled Robot Based on a Laser Scanner Sensor
Sensors 2015, 15, 9681-9702; doi:10.3390/s150509681 Article OPEN ACCESS sensors ISSN 1424-8220 www.mdpi.com/journal/sensors Analysis and Experimental Kinematics of a Skid-Steering Wheeled Robot Based on
More informationMotion Control (wheeled robots)
3 Motion Control (wheeled robot) Requirement for Motion Control Kinematic / dynamic model of the robot Model of the interaction between the wheel and the ground Definition of required motion -> peed control,
More informationDYNAMIC TRIANGULATION FOR MOBILE ROBOT LOCALIZATION USING AN ANGULAR STATE KALMAN FILTER. Josep Maria Font, Joaquim A. Batlle
DYNAMIC TRIANGULATION FOR MOBILE ROBOT LOCALIZATION USING AN ANGULAR STATE KALMAN FILTER Josep Maria Font, Joaquim A. Batlle Department of Mechanical Engineering Technical University of Catalonia (UPC)
More informationExperimental Evaluation of an Encoder Trailer for Dead-reckoning in Tracked Mobile Robots
Experimental Evaluation of an Encoder Trailer for Dead-reckoning in Tracked Mobile Robots Zhejun Fan* Johann Borenstein* David Wehe** Yoram Koren* *Department of Mechanical Engineering and Applied Mechanics
More informationModeling of Wheeled Mobile Robots using Dextrous Manipulation Kinematics
Modeling of Wheeled Mobile Robots using Dextrous Manipulation Kinematics Joseph Auchter, Carl Moore, Ashitava Ghosal Abstract This document introduces a new kinematic simulation of a wheeled mobile robot
More informationConstruction and Calibration of a Low-Cost 3D Laser Scanner with 360º Field of View for Mobile Robots
Construction and Calibration of a Low-Cost 3D Laser Scanner with 360º Field of View for Mobile Robots Jorge L. Martínez, Jesús Morales, Antonio, J. Reina, Anthony Mandow, Alejandro Pequeño-Boter*, and
More information5 Mobile Robot Localization
5 Mobile Robot Localization 159 5 Mobile Robot Localization 5.1 Introduction? Fig 5.1 Where am I? Navigation is one of the most challenging competencies required of a mobile robot. Success in navigation
More informationExperimental Verification of Stability Region of Balancing a Single-wheel Robot: an Inverted Stick Model Approach
IECON-Yokohama November 9-, Experimental Verification of Stability Region of Balancing a Single-wheel Robot: an Inverted Stick Model Approach S. D. Lee Department of Mechatronics Engineering Chungnam National
More informationODOMETRY CORRECTION OF A MOBILE ROBOT USING A RANGE-FINDING LASER. A Thesis Presented to the Graduate School of Clemson University
ODOMETRY CORRECTION OF A MOBILE ROBOT USING A RANGE-FINDING LASER A Thesis Presented to the Graduate School of Clemson University In Partial Fulfillment of the Requirements for the Degree Master of Science
More informationApproximating Kinematics for Tracked Mobile Robots
J. L. Martínez A. Mandow J. Morales S. Pedraza A. García-Cerezo Dept. Ingeniería de Sistemas y Automática Universidad de Málaga Plaza El Ejido s/n, 29013-Málaga, Spain jlmartinez@uma.es Approximating Kinematics
More informationRobotics Project. Final Report. Computer Science University of Minnesota. December 17, 2007
Robotics Project Final Report Computer Science 5551 University of Minnesota December 17, 2007 Peter Bailey, Matt Beckler, Thomas Bishop, and John Saxton Abstract: A solution of the parallel-parking problem
More informationSoftware Driver for Differential Drive Rovers. Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo
Software Driver for Differential Drive Rovers Corso di Robotica Prof. Davide Brugali Università degli Studi di Bergamo Robot BART Motors with Encoders SONAR sensors Radio module Line color sensor 2 UNIBG
More informationPrecise indoor localization of multiple mobile robots with adaptive sensor fusion using odometry and vision data
Preprints of the 9th World Congress The International Federation of Automatic Control Cape Town, South Africa. August 4-9, 04 Precise indoor localization of multiple mobile robots with adaptive sensor
More informationUncertainties: Representation and Propagation & Line Extraction from Range data
41 Uncertainties: Representation and Propagation & Line Extraction from Range data 42 Uncertainty Representation Section 4.1.3 of the book Sensing in the real world is always uncertain How can uncertainty
More informationTesting the Possibilities of Using IMUs with Different Types of Movements
137 Testing the Possibilities of Using IMUs with Different Types of Movements Kajánek, P. and Kopáčik A. Slovak University of Technology, Faculty of Civil Engineering, Radlinského 11, 81368 Bratislava,
More informationAbsolute Scale in Structure from Motion from a Single Vehicle Mounted Camera by Exploiting Nonholonomic Constraints
Absolute Scale in Structure from Motion from a Single Vehicle Mounted Camera by Exploiting Nonholonomic Constraints Davide Scaramuzza 1, Friedrich Fraundorfer 2, Marc Pollefeys 2, Roland Siegwart 1 1 Autonomous
More informationOdometry and Calibration Methods for Multi-Castor Vehicles
008 IEEE International Conference on Robotics and Automation Pasadena, CA, USA, May 9-3, 008 Odometry and Calibration Methods for Multi-Castor Vehicles James Doebbler, Jeremy J Davis, John L Junkins, and
More informationOn Differential Drive Robot Odometry with Application to Path Planning
Proceedings of the European Control Conference 2007 Kos, Greece, July 2-5, 2007 On ifferential rive Robot Odometry with Application to Path Planning Evangelos Papadopoulos and Michael Misailidis Abstract
More informationStructure from Motion. Prof. Marco Marcon
Structure from Motion Prof. Marco Marcon Summing-up 2 Stereo is the most powerful clue for determining the structure of a scene Another important clue is the relative motion between the scene and (mono)
More informationNonholonomic motion planning for car-like robots
Nonholonomic motion planning for car-like robots A. Sánchez L. 2, J. Abraham Arenas B. 1, and René Zapata. 2 1 Computer Science Dept., BUAP Puebla, Pue., México {aarenas}@cs.buap.mx 2 LIRMM, UMR5506 CNRS,
More informationOdometry Correction for Humanoid Robots Using Optical Sensors
Odometry Correction for Humanoid Robots Using Optical Sensors Stefan Czarnetzki, Maximilian Hegele, and Sören Kerner Robotics Research Institute Section Information Technology TU Dortmund University 44221
More informationTorque Distribution and Slip Minimization in an Omnidirectional Mobile Base
Torque Distribution and Slip Minimization in an Omnidirectional Mobile Base Yuan Ping Li, Denny Oetomo, Marcelo H. Ang Jr.* National University of Singapore 1 ent Ridge Crescent, Singapore 1196 *mpeangh@nus.edu.sg
More information