Correcting INS Drift in Terrain Surface Measurements. Heather Chemistruck Ph.D. Student Mechanical Engineering Vehicle Terrain Performance Lab

Size: px
Start display at page:

Download "Correcting INS Drift in Terrain Surface Measurements. Heather Chemistruck Ph.D. Student Mechanical Engineering Vehicle Terrain Performance Lab"

Transcription

1 Correcting INS Drift in Terrain Surface Measurements Ph.D. Student Mechanical Engineering Vehicle Terrain Performance Lab October 25, 2010

2 Outline Laboratory Overview Vehicle Terrain Measurement System Addressing the Problem Correcting INS Drift in Terrain Measurements Conclusions Slide 2 2

3 Laboratory Overview Vehicles Passenger cars, commercial off-road, military vehicles, motorcycles (system level) Modeling and Simulation Terrain Modeling Measurement Performance Ride Handling Reliability Durability Slide 3 3

4 Vehicle Terrain Measurement System Scanning Laser Provides relative height measurement Inertial Navigation System (INS) Differential GPS: Establishes global coordinate system Inertial Measurement Unit (IMU): Mitigates body motion Slide 4 4

5 VTMS: Digital Signal Processing Body Motion Cancellation VTMS rear wheels VTMS on curb off curb Raw Laser Ins Z Measured Profile Profile height (m) Slide Time(secs) x

6 VTMS: Coordinate System Horizontal Plane Map point-cloud data to uniform grid Defined by Vehicle Path (u) Slide 6 6

7 VTMS: Coordinate System Terrain Height i: longitudinal location of transverse profile, where i {0,1,,m} j: transverse location of longitudinal profile, where j {0,1,,n} k: realization (measurement), where k Slide 7 {1,2,,r} 7

8 Addressing the Problem INS is capable of a establishing a geodetic (latitude & longitude) position with 2cm accuracy with differential GPS Experimentation shows artifacts of INS drift Max variation is +/- 10mm in elliptical height Terrain Height, m GPS Elliptical Height, mm INS Drift introduces run-to-run variation ± 10mm GPS Time, s ± 10mm Longitudinal Distance, m Slide 8 8

9 Correcting INS Drift Assumptions Elliptical height changes only in time Drift is the same within each scan (~1ms) Correct from scan to scan Non-deformable terrain only INS treated as black box combining DGPS + IMU Slide 9 9

10 Correcting INS Drift Decomposing the Vector Space Measured Surface : z i,k True Surface: s i = + Total Error: e i,k Slide 10 10

11 Correcting INS Drift Error Modeling Total Error = Drift + Noise Global Error (Drift) Drift (m) Random Walk Process ±10mm INS Drift: δ i,k,l Longitudinal Distance, m Local Error (Noise) + = Total Error: e i,k 2 x 10-3 noise Zero Mean Process Noise: n i,k Slide 11 Amplitude, [meters] ±1mm Longitudinal Distance, [meters]

12 Correcting INS Drift The Total error must be separated into INS drift and noise Singular Value Decomposition determine contributions from different shapes to the error Noise must be zero-mean and is not correlated 0.3 to the INS drift Amplitude st Basis Vector 2nd Basis Vector Slide Length of Vector space, n 12

13 Correcting INS Drift Proof of Concept MnRoad Test Facility, Albertville, MN 160m section of asphalt, 100mm spacing i=[1,2 1518] 10 total measurements (alternating directions) k=[1,2 10] Slide 13 13

14 Correcting INS Drift Proof of Concept Two basis vectors imply E[n ik ]=0 First Basis Vector= Constant Offset Second Basis Vector = Slope Offset 0.3 Singular Values Amplitude Slide 14 Length of Vector space, n Transverse Index, j 1st Basis Vector 2nd Basis Vector 14

15 Correcting INS Drift Proof of Concept Longitudinal view of terrain surface Terrain Height, [meters] No INS Drift Correction Profile Profile 2 Profile Profile 4 Profile Profile 6 Profile 7 Profile Profile 9 Profile Longitduinal Distance, [meters] Terrain Height, [meters] Basis Vectors Profile Profile Profile 3 Profile Profile 5 Profile Profile 7 Profile Profile 9 Profile 10 True Surface Longitudinal Distance, [meters] Slide 15 15

16 Conclusions INS Drift sufficiently characterized and removed Set of basis vectors identified 1 st Basis Vector = Elevation Principal Direction 2 nd Basis Vector = Bank Angle Principal Direction Drift is a random walk process Noise is a zero-mean process Variation in measured surfaces reduced to 1mm True Surface established Slide 16 16

Removing Drift from Inertial Navigation System Measurements RPUG Robert Binns Mechanical Engineering Vehicle Terrain Performance Lab

Removing Drift from Inertial Navigation System Measurements RPUG Robert Binns Mechanical Engineering Vehicle Terrain Performance Lab Removing Drift from Inertial Navigation System Measurements RPUG 2009 Mechanical Engineering Vehicle Terrain Performance Lab December 10, 2009 Outline Laboratory Overview Vehicle Terrain Measurement System

More information

AN APPROACH TO DEVELOPING A REFERENCE PROFILER

AN APPROACH TO DEVELOPING A REFERENCE PROFILER AN APPROACH TO DEVELOPING A REFERENCE PROFILER John B. Ferris TREY Associate SMITH Professor Graduate Mechanical Research Engineering Assistant Virginia Tech RPUG October Meeting 08 October 28, 2008 Overview

More information

Terrain Characterization

Terrain Characterization Terrain Characterization Make Everything as Simple as Possible, but not Simpler or A Model-Portable, Compact, Physically Meaningful Characterization of Terrain Surfaces John B. Ferris, Mechanical Engineering

More information

ROAD SURFACE STRUCTURE MONITORING AND ANALYSIS USING HIGH PRECISION GPS MOBILE MEASUREMENT SYSTEMS (MMS)

ROAD SURFACE STRUCTURE MONITORING AND ANALYSIS USING HIGH PRECISION GPS MOBILE MEASUREMENT SYSTEMS (MMS) ROAD SURFACE STRUCTURE MONITORING AND ANALYSIS USING HIGH PRECISION GPS MOBILE MEASUREMENT SYSTEMS (MMS) Bonifacio R. Prieto PASCO Philippines Corporation, Pasig City, 1605, Philippines Email: bonifacio_prieto@pascoph.com

More information

Vehicle Localization. Hannah Rae Kerner 21 April 2015

Vehicle Localization. Hannah Rae Kerner 21 April 2015 Vehicle Localization Hannah Rae Kerner 21 April 2015 Spotted in Mtn View: Google Car Why precision localization? in order for a robot to follow a road, it needs to know where the road is to stay in a particular

More information

Improved Methods for Gridding, Stochastic Modeling, and Compact Characterization of Terrain Surfaces

Improved Methods for Gridding, Stochastic Modeling, and Compact Characterization of Terrain Surfaces Improved Methods for Gridding, Stochastic Modeling, and Compact Characterization of Terrain Surfaces Jacob N. Lambeth Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University

More information

Evaluating the Performance of a Vehicle Pose Measurement System

Evaluating 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 information

Airborne Laser Scanning: Remote Sensing with LiDAR

Airborne Laser Scanning: Remote Sensing with LiDAR Airborne Laser Scanning: Remote Sensing with LiDAR ALS / LIDAR OUTLINE Laser remote sensing background Basic components of an ALS/LIDAR system Two distinct families of ALS systems Waveform Discrete Return

More information

Sensory Augmentation for Increased Awareness of Driving Environment

Sensory Augmentation for Increased Awareness of Driving Environment Sensory Augmentation for Increased Awareness of Driving Environment Pranay Agrawal John M. Dolan Dec. 12, 2014 Technologies for Safe and Efficient Transportation (T-SET) UTC The Robotics Institute Carnegie

More information

Performance Evaluation of Optech's ALTM 3100: Study on Geo-Referencing Accuracy

Performance Evaluation of Optech's ALTM 3100: Study on Geo-Referencing Accuracy Performance Evaluation of Optech's ALTM 3100: Study on Geo-Referencing Accuracy R. Valerie Ussyshkin, Brent Smith, Artur Fidera, Optech Incorporated BIOGRAPHIES Dr. R. Valerie Ussyshkin obtained a Ph.D.

More information

OPTIMIZING 3D SURFACE CHARACTERISTICS DATA COLLECTION BY RE-USING THE DATA FOR PROJECT LEVEL ROAD DESIGN

OPTIMIZING 3D SURFACE CHARACTERISTICS DATA COLLECTION BY RE-USING THE DATA FOR PROJECT LEVEL ROAD DESIGN OPTIMIZING 3D SURFACE CHARACTERISTICS DATA COLLECTION BY RE-USING THE DATA FOR PROJECT LEVEL ROAD DESIGN Benoit Petitclerc, P.E. John Laurent, M. Sc Richard Habel, M. Sc., Pavemetrics Systems Inc., Canada

More information

DIGITAL ROAD PROFILE USING KINEMATIC GPS

DIGITAL ROAD PROFILE USING KINEMATIC GPS ARTIFICIAL SATELLITES, Vol. 44, No. 3 2009 DOI: 10.2478/v10018-009-0023-6 DIGITAL ROAD PROFILE USING KINEMATIC GPS Ashraf Farah Assistant Professor, Aswan-Faculty of Engineering, South Valley University,

More information

Real Time Multi-Sensor Data Acquisition and Processing for a Road Mapping System

Real Time Multi-Sensor Data Acquisition and Processing for a Road Mapping System Real Time Multi-Sensor Data Acquisition and Processing for a Road Mapping System by Xiang Luo A thesis submitted for the degree of Master of Engineering (Research) Faculty of Engineering and Information

More information

Introduction to Inertial Navigation (INS tutorial short)

Introduction to Inertial Navigation (INS tutorial short) Introduction to Inertial Navigation (INS tutorial short) Note 1: This is a short (20 pages) tutorial. An extended (57 pages) tutorial that also includes Kalman filtering is available at http://www.navlab.net/publications/introduction_to

More information

SUMMARY. Page INTERIOR SURVEY - SAN FRANCESCO CHURCH (TERNI) EXTERIOR SURVEY - UFFIZI & PIAZZA DUOMO TUNNEL SURVEY TERNI

SUMMARY. Page INTERIOR SURVEY - SAN FRANCESCO CHURCH (TERNI) EXTERIOR SURVEY - UFFIZI & PIAZZA DUOMO TUNNEL SURVEY TERNI CASE STUDIES SUMMARY Page INTERIOR SURVEY - SAN FRANCESCO CHURCH (TERNI) EXTERIOR SURVEY - UFFIZI & PIAZZA DUOMO TUNNEL SURVEY TERNI FOREST SURVEY - MARMORE WATERFALLS ROAD SURVEY FERRARA 3 4 5 6 7 2 INTERIOR

More information

W4. Perception & Situation Awareness & Decision making

W4. Perception & Situation Awareness & Decision making W4. Perception & Situation Awareness & Decision making Robot Perception for Dynamic environments: Outline & DP-Grids concept Dynamic Probabilistic Grids Bayesian Occupancy Filter concept Dynamic Probabilistic

More information

Airborne LiDAR Data Acquisition for Forestry Applications. Mischa Hey WSI (Corvallis, OR)

Airborne LiDAR Data Acquisition for Forestry Applications. Mischa Hey WSI (Corvallis, OR) Airborne LiDAR Data Acquisition for Forestry Applications Mischa Hey WSI (Corvallis, OR) WSI Services Corvallis, OR Airborne Mapping: Light Detection and Ranging (LiDAR) Thermal Infrared Imagery 4-Band

More information

POINT CLOUD ANALYSIS FOR ROAD PAVEMENTS IN BAD CONDITIONS INTRODUCTION

POINT CLOUD ANALYSIS FOR ROAD PAVEMENTS IN BAD CONDITIONS INTRODUCTION POINT CLOUD ANALYSIS FOR ROAD PAVEMENTS IN BAD CONDITIONS Yoshiyuki Yamamoto, Associate Professor Yasuhiro Shimizu, Doctoral Student Eiji Nakamura, Professor Masayuki Okugawa, Associate Professor Aichi

More information

1. LiDAR System Description and Specifications

1. LiDAR System Description and Specifications High Point Density LiDAR Survey of Mayapan, MX PI: Timothy S. Hare, Ph.D. Timothy S. Hare, Ph.D. Associate Professor of Anthropology Institute for Regional Analysis and Public Policy Morehead State University

More information

TECHNIQUES FOR USING 3D TERRAIN SURFACE MEASUREMENTS FOR VEHICULAR SIMULATIONS

TECHNIQUES FOR USING 3D TERRAIN SURFACE MEASUREMENTS FOR VEHICULAR SIMULATIONS TECHNIQUES FOR USING 3D TERRAIN SURFACE MEASUREMENTS FOR VEHICULAR SIMULATIONS Zachary Ray Detweiler Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial

More information

William E. Dietrich Professor 313 McCone Phone Fax (fax)

William E. Dietrich Professor 313 McCone Phone Fax (fax) February 13, 2007. Contact information William E. Dietrich Professor 313 McCone Phone 510-642-2633 Fax 510-643-9980 (fax) bill@eps.berkeley.edu Project location: Northwest of the Golden Gate Bridge, San

More information

Controllable Suspension Design Using Magnetorheological Fluid

Controllable Suspension Design Using Magnetorheological Fluid Controllable Suspension Design Using Magnetorheological Fluid Public Defence October 213 Student: Supervisor: Co-Supervisor: Anria Strydom Prof Schalk Els Dr Sudhir Kaul 1 Outline Project background MR

More information

Satellite Attitude Determination

Satellite Attitude Determination Satellite Attitude Determination AERO4701 Space Engineering 3 Week 5 Last Week Looked at GPS signals and pseudorange error terms Looked at GPS positioning from pseudorange data Looked at GPS error sources,

More information

MULTI-BODY VEHICLE DYNAMICS SIMULATION BASED ON MEASURED 3D TERRAIN DATA

MULTI-BODY VEHICLE DYNAMICS SIMULATION BASED ON MEASURED 3D TERRAIN DATA MULTI-BODY VEHICLE DYNAMICS SIMULATION BASED ON MEASURED 3D TERRAIN DATA Tejas Varunjikar Graduate Student, Department of Mechanical and Nuclear Engineering, The Pennsylvania State University, University

More information

Tightly-Integrated Visual and Inertial Navigation for Pinpoint Landing on Rugged Terrains

Tightly-Integrated Visual and Inertial Navigation for Pinpoint Landing on Rugged Terrains Tightly-Integrated Visual and Inertial Navigation for Pinpoint Landing on Rugged Terrains PhD student: Jeff DELAUNE ONERA Director: Guy LE BESNERAIS ONERA Advisors: Jean-Loup FARGES Clément BOURDARIAS

More information

Mobile 3D laser scanning technology application in the surveying of urban underground rail transit

Mobile 3D laser scanning technology application in the surveying of urban underground rail transit IOP Conference Series: Earth and Environmental Science PAPER OPEN ACCESS Mobile 3D laser scanning technology application in the surveying of urban underground rail transit To cite this article: Youmei

More information

Technical Bulletin Global Vehicle Target Specification Version 1.0 May 2018 TB 025

Technical Bulletin Global Vehicle Target Specification Version 1.0 May 2018 TB 025 Technical Bulletin Global Vehicle Target Specification Version 1.0 May 2018 TB 025 Title Global Vehicle Target Specification Version 1.0 Document Number TB025 Author Euro NCAP Secretariat Date May 2018

More information

Mapping Project Report Table of Contents

Mapping Project Report Table of Contents LiDAR Estimation of Forest Leaf Structure, Terrain, and Hydrophysiology Airborne Mapping Project Report Principal Investigator: Katherine Windfeldt University of Minnesota-Twin cities 115 Green Hall 1530

More information

Using 3D Laser Range Data for SLAM in Outdoor Environments

Using 3D Laser Range Data for SLAM in Outdoor Environments Using 3D Laser Range Data for SLAM in Outdoor Environments Christian Brenneke, Oliver Wulf, Bernardo Wagner Institute for Systems Engineering, University of Hannover, Germany [brenneke, wulf, wagner]@rts.uni-hannover.de

More information

A Comparison of Laser Scanners for Mobile Mapping Applications

A Comparison of Laser Scanners for Mobile Mapping Applications A Comparison of Laser Scanners for Mobile Mapping Applications Craig Glennie 1, Jerry Dueitt 2 1 Department of Civil & Environmental Engineering The University of Houston 3605 Cullen Boulevard, Room 2008

More information

Terrain Modeling and Mapping for Telecom Network Installation Using Scanning Technology. Maziana Muhamad

Terrain Modeling and Mapping for Telecom Network Installation Using Scanning Technology. Maziana Muhamad Terrain Modeling and Mapping for Telecom Network Installation Using Scanning Technology Maziana Muhamad Summarising LiDAR (Airborne Laser Scanning) LiDAR is a reliable survey technique, capable of: acquiring

More information

NATIONWIDE POINT CLOUDS AND 3D GEO- INFORMATION: CREATION AND MAINTENANCE GEORGE VOSSELMAN

NATIONWIDE POINT CLOUDS AND 3D GEO- INFORMATION: CREATION AND MAINTENANCE GEORGE VOSSELMAN NATIONWIDE POINT CLOUDS AND 3D GEO- INFORMATION: CREATION AND MAINTENANCE GEORGE VOSSELMAN OVERVIEW National point clouds Airborne laser scanning in the Netherlands Quality control Developments in lidar

More information

An Experimental Exploration of Low-Cost Solutions for Precision Ground Vehicle Navigation

An 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 information

Pattern Recognition for Autonomous. Pattern Recognition for Autonomous. Driving. Freie Universität t Berlin. Raul Rojas

Pattern Recognition for Autonomous. Pattern Recognition for Autonomous. Driving. Freie Universität t Berlin. Raul Rojas Pattern Recognition for Autonomous Pattern Recognition for Autonomous Driving Raul Rojas Freie Universität t Berlin FU Berlin Berlin 3d model from Berlin Partner Freie Universitaet Berlin Outline of the

More information

FEATURE EXTRACTION FROM RANGE DATA

FEATURE EXTRACTION FROM RANGE DATA FEATURE EXTRACTION FROM RANGE DATA Dinesh MANANDHAR, Ryosuke SHIBASAKI Centre for Spatial Information Science, The University of Tokyo 4-6-1, Komaba, Meguro-ku, Tokyo 153-8505, JAPAN Tel / Fax No: 81-3-5452-6417

More information

TEST RESULTS OF A GPS/INERTIAL NAVIGATION SYSTEM USING A LOW COST MEMS IMU

TEST RESULTS OF A GPS/INERTIAL NAVIGATION SYSTEM USING A LOW COST MEMS IMU TEST RESULTS OF A GPS/INERTIAL NAVIGATION SYSTEM USING A LOW COST MEMS IMU Alison K. Brown, Ph.D.* NAVSYS Corporation, 1496 Woodcarver Road, Colorado Springs, CO 891 USA, e-mail: abrown@navsys.com Abstract

More information

Chapter 4 Dynamics. Part Constrained Kinematics and Dynamics. Mobile Robotics - Prof Alonzo Kelly, CMU RI

Chapter 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 information

Chapters 1 9: Overview

Chapters 1 9: Overview Chapters 1 9: Overview Chapter 1: Introduction Chapters 2 4: Data acquisition Chapters 5 9: Data manipulation Chapter 5: Vertical imagery Chapter 6: Image coordinate measurements and refinements Chapters

More information

Chapters 1 7: Overview

Chapters 1 7: Overview Chapters 1 7: Overview Photogrammetric mapping: introduction, applications, and tools GNSS/INS-assisted photogrammetric and LiDAR mapping LiDAR mapping: principles, applications, mathematical model, and

More information

Runway Centerline Deviation Estimation from Point Clouds using LiDAR imagery

Runway Centerline Deviation Estimation from Point Clouds using LiDAR imagery Runway Centerline Deviation Estimation from Point Clouds using LiDAR imagery Seth Young 1, Charles Toth 2, Zoltan Koppanyi 2 1 Department of Civil, Environmental and Geodetic Engineering The Ohio State

More information

HAWAII KAUAI Survey Report. LIDAR System Description and Specifications

HAWAII KAUAI Survey Report. LIDAR System Description and Specifications HAWAII KAUAI Survey Report LIDAR System Description and Specifications This survey used an Optech GEMINI Airborne Laser Terrain Mapper (ALTM) serial number 06SEN195 mounted in a twin-engine Navajo Piper

More information

GI-Eye II GPS/Inertial System For Target Geo-Location and Image Geo-Referencing

GI-Eye II GPS/Inertial System For Target Geo-Location and Image Geo-Referencing GI-Eye II GPS/Inertial System For Target Geo-Location and Image Geo-Referencing David Boid, Alison Brown, Ph. D., Mark Nylund, Dan Sullivan NAVSYS Corporation 14960 Woodcarver Road, Colorado Springs, CO

More information

High-Precision Positioning Unit 2.2 Student Exercise: Calculating Topographic Change

High-Precision Positioning Unit 2.2 Student Exercise: Calculating Topographic Change High-Precision Positioning Unit 2.2 Student Exercise: Calculating Topographic Change Ian Lauer and Ben Crosby (Idaho State University) Change is an inevitable part of our natural world and varies as a

More information

Aided-inertial for Long-term, Self-contained GPS-denied Navigation and Mapping

Aided-inertial for Long-term, Self-contained GPS-denied Navigation and Mapping Aided-inertial for Long-term, Self-contained GPS-denied Navigation and Mapping Erik Lithopoulos, Louis Lalumiere, Ron Beyeler Applanix Corporation Greg Spurlock, LTC Bruce Williams Defense Threat Reduction

More information

An Introduction to Lidar & Forestry May 2013

An Introduction to Lidar & Forestry May 2013 An Introduction to Lidar & Forestry May 2013 Introduction to Lidar & Forestry Lidar technology Derivatives from point clouds Applied to forestry Publish & Share Futures Lidar Light Detection And Ranging

More information

Prepared for: CALIFORNIA COAST COMMISSION c/o Dr. Stephen Schroeter 45 Fremont Street, Suite 2000 San Francisco, CA

Prepared for: CALIFORNIA COAST COMMISSION c/o Dr. Stephen Schroeter 45 Fremont Street, Suite 2000 San Francisco, CA REVIEW OF MULTIBEAM SONAR SURVEYS WHEELER REEF NORTH, SAN CLEMENTE, CALIFORNIA TO EVALUATE ACCURACY AND PRECISION OF REEF FOOTPRINT DETERMINATIONS AND CHANGES BETWEEN 2008 AND 2009 SURVEYS Prepared for:

More information

Purpose : Understanding Projections, 12D, and the System 1200.

Purpose : Understanding Projections, 12D, and the System 1200. Purpose : Understanding Projections, 12D, and the System 1200. 1. For any Cad work created inside 12D, the distances entered are plane (Horizontal Chord) distances. 2. Setting a projection, or changing

More information

DYNAMIC POSITIONING CONFERENCE September 16-17, Sensors

DYNAMIC POSITIONING CONFERENCE September 16-17, Sensors DYNAMIC POSITIONING CONFERENCE September 16-17, 2003 Sensors An Integrated acoustic positioning and inertial navigation system Jan Erik Faugstadmo, Hans Petter Jacobsen Kongsberg Simrad, Norway Revisions

More information

Federica Zampa Sineco SpA V. le Isonzo, 14/1, Milan, 20135, Italy

Federica Zampa Sineco SpA V. le Isonzo, 14/1, Milan, 20135, Italy LYNX MOBILE MAPPER TM : THE NEW SURVEY TECHNOLOGY Federica Zampa Sineco SpA V. le Isonzo, 14/1, Milan, 20135, Italy federica.zampa@sineco.co.it Dario Conforti Optech Incorporated 300 Interchange Way, Vaughan,

More information

ROAD-SCANNER COMPACT APPLICATION FIELDS MAIN FEATURES

ROAD-SCANNER COMPACT APPLICATION FIELDS MAIN FEATURES ROAD-SCANNER COMPACT Mobile Mapping System by GEXCEL & SITECO collaboration A smaller mobile system for asset management and cartography suited for ZOLLER & FRÖHLICH PROFILER 9012 laser scanner. 2 + 3

More information

Rigorous Scan Data Adjustment for kinematic LIDAR systems

Rigorous Scan Data Adjustment for kinematic LIDAR systems Rigorous Scan Data Adjustment for kinematic LIDAR systems Paul Swatschina Riegl Laser Measurement Systems ELMF Amsterdam, The Netherlands 13 November 2013 www.riegl.com Contents why kinematic scan data

More information

Automating Data Accuracy from Multiple Collects

Automating Data Accuracy from Multiple Collects Automating Data Accuracy from Multiple Collects David JANSSEN, Canada Key words: lidar, data processing, data alignment, control point adjustment SUMMARY When surveyors perform a 3D survey over multiple

More information

Geocoding and Georeferencing. Scott Bell GIS Institute

Geocoding and Georeferencing. Scott Bell GIS Institute Geocoding and Georeferencing Scott Bell GIS Institute Learning Outcomes Define coordinate system and map projection Relate coordinate systems and map projections Distinguish between defining and changing

More information

ENY-C2005 Geoinformation in Environmental Modeling Lecture 4b: Laser scanning

ENY-C2005 Geoinformation in Environmental Modeling Lecture 4b: Laser scanning 1 ENY-C2005 Geoinformation in Environmental Modeling Lecture 4b: Laser scanning Petri Rönnholm Aalto University 2 Learning objectives To recognize applications of laser scanning To understand principles

More information

Measuring a Centre of Gravity of an Object using 4 Load Transducer Method

Measuring a Centre of Gravity of an Object using 4 Load Transducer Method Measuring a Centre of Gravity of an Object using 4 Load Transducer Method Sandip G. Patel Jainish J. Topiwala Assistant Professor, Mechanical Engg. Department Assistant Professor, Mechanical Engg. Department

More information

DriftLess Technology to improve inertial sensors

DriftLess Technology to improve inertial sensors Slide 1 of 19 DriftLess Technology to improve inertial sensors Marcel Ruizenaar, TNO marcel.ruizenaar@tno.nl Slide 2 of 19 Topics Problem, Drift in INS due to bias DriftLess technology What is it How it

More information

TerraMatch. Introduction

TerraMatch. Introduction TerraMatch Introduction Error sources Interior in LRF Why TerraMatch? Errors in laser distance measurement Scanning mirror errors Exterior in trajectories Errors in position (GPS) Errors in orientation

More information

Use of n-vector for Radar Applications

Use of n-vector for Radar Applications Use of n-vector for Radar Applications Nina Ødegaard, Kenneth Gade Norwegian Defence Research Establishment Kjeller, NORWAY email: Nina.Odegaard@ffi.no Kenneth.Gade@ffi.no Abstract: This paper aims to

More information

Motion estimation of unmanned marine vehicles Massimo Caccia

Motion estimation of unmanned marine vehicles Massimo Caccia Motion estimation of unmanned marine vehicles Massimo Caccia Consiglio Nazionale delle Ricerche Istituto di Studi sui Sistemi Intelligenti per l Automazione Via Amendola 122 D/O, 70126, Bari, Italy massimo.caccia@ge.issia.cnr.it

More information

LiDAR for Urban Change Detection. Keith W. Cunningham, PhD Alaska Satellite Facility November 13, 2009

LiDAR for Urban Change Detection. Keith W. Cunningham, PhD Alaska Satellite Facility November 13, 2009 LiDAR for Urban Change Detection Keith W. Cunningham, PhD Alaska Satellite Facility November 13, 2009 LiDAR LiDAR Light Detection and Ranging Building Footprints GIS outlines (planimetrics) GIS Geographic

More information

Cross Slope Collection using Mobile Lidar

Cross Slope Collection using Mobile Lidar Cross Slope Collection using Mobile Lidar ACEC/SCDOT Annual Meeting December 2, 2015 Introduction Adequate cross slopes on South Carolina Interstates result in: Proper drainage Enhance driver safety by

More information

EE 570: Location and Navigation: Theory & Practice

EE 570: Location and Navigation: Theory & Practice EE 570: Location and Navigation: Theory & Practice Navigation Sensors and INS Mechanization Thursday 14 Feb 2013 NMT EE 570: Location and Navigation: Theory & Practice Slide 1 of 14 Inertial Sensor Modeling

More information

Camera Drones Lecture 2 Control and Sensors

Camera Drones Lecture 2 Control and Sensors Camera Drones Lecture 2 Control and Sensors Ass.Prof. Friedrich Fraundorfer WS 2017 1 Outline Quadrotor control principles Sensors 2 Quadrotor control - Hovering Hovering means quadrotor needs to hold

More information

> Acoustical feedback in the form of a beep with increasing urgency with decreasing distance to an obstacle

> Acoustical feedback in the form of a beep with increasing urgency with decreasing distance to an obstacle PARKING ASSIST TESTING THE MEASURABLE DIFFERENCE. > Creation of complex 2-dimensional objects > Online distance calculations between moving and stationary objects > Creation of Automatic Points of Interest

More information

Advanced point cloud processing

Advanced point cloud processing Advanced point cloud processing George Vosselman ITC Enschede, the Netherlands INTERNATIONAL INSTITUTE FOR GEO-INFORMATION SCIENCE AND EARTH OBSERVATION Laser scanning platforms Airborne systems mounted

More information

TLS Parameters, Workflows and Field Methods

TLS Parameters, Workflows and Field Methods TLS Parameters, Workflows and Field Methods Marianne Okal, UNAVCO GSA, October 20 th, 2017 How a Lidar instrument works (Recap) Transmits laser signals and measures the reflected light to create 3D point

More information

ACTIVITY TWO CONSTANT VELOCITY IN TWO DIRECTIONS

ACTIVITY TWO CONSTANT VELOCITY IN TWO DIRECTIONS 1 ACTIVITY TWO CONSTANT VELOCITY IN TWO DIRECTIONS Purpose The overall goal of this activity is for students to analyze the motion of an object moving with constant velocity along a diagonal line. In this

More information

New Features in TerraScan. Arttu Soininen Software developer Terrasolid Ltd

New Features in TerraScan. Arttu Soininen Software developer Terrasolid Ltd New Features in TerraScan Arttu Soininen Software developer Terrasolid Ltd Default Coordinate Setup Default coordinate setup category added to Settings Defines coordinate setup to use if you open a design

More information

Humanoid Robotics. Monte Carlo Localization. Maren Bennewitz

Humanoid Robotics. Monte Carlo Localization. Maren Bennewitz Humanoid Robotics Monte Carlo Localization Maren Bennewitz 1 Basis Probability Rules (1) If x and y are independent: Bayes rule: Often written as: The denominator is a normalizing constant that ensures

More information

Sensor Fusion: Potential, Challenges and Applications. Presented by KVH Industries and Geodetics, Inc. December 2016

Sensor Fusion: Potential, Challenges and Applications. Presented by KVH Industries and Geodetics, Inc. December 2016 Sensor Fusion: Potential, Challenges and Applications Presented by KVH Industries and Geodetics, Inc. December 2016 1 KVH Industries Overview Innovative technology company 600 employees worldwide Focused

More information

S7316: Real-Time Robotics Control and Simulation for Deformable Terrain Applications Using the GPU

S7316: Real-Time Robotics Control and Simulation for Deformable Terrain Applications Using the GPU S7316: Real-Time Robotics Control and Simulation for Deformable Terrain Applications Using the GPU Daniel Melanz Copyright 2017 Energid Technology Overview 1. Who are we? 2. What do we do? 3. How do we

More information

Terrafirma: a Pan-European Terrain motion hazard information service.

Terrafirma: a Pan-European Terrain motion hazard information service. Terrafirma: a Pan-European Terrain motion hazard information service www.terrafirma.eu.com The Future of Terrafirma - Wide Area Product Nico Adam and Alessandro Parizzi DLR Oberpfaffenhofen Terrafirma

More information

Terrain Roughness Identification for High-Speed UGVs

Terrain Roughness Identification for High-Speed UGVs Proceedings of the International Conference of Control, Dynamic Systems, and Robotics Ottawa, Ontario, Canada, May 15-16 2014 Paper No. 11 Terrain Roughness Identification for High-Speed UGVs Graeme N.

More information

TEST EXAM PART 2 INTERMEDIATE LAND NAVIGATION

TEST EXAM PART 2 INTERMEDIATE LAND NAVIGATION NAME DATE TEST EXAM PART 2 INTERMEDIATE LAND NAVIGATION 1. Knowing these four basic skills, it is impossible to be totally lost; what are they? a. Track Present Location / Determine Distance / Sense of

More information

Airborne Hyperspectral Imaging Using the CASI1500

Airborne Hyperspectral Imaging Using the CASI1500 Airborne Hyperspectral Imaging Using the CASI1500 AGRISAR/EAGLE 2006, ITRES Research CASI 1500 overview A class leading VNIR sensor with extremely sharp optics. 380 to 1050nm range 288 spectral bands ~1500

More information

Phone: Fax: Table of Contents

Phone: Fax: Table of Contents Geomorphic Characterization of Precarious Rock Zones LIDAR Mapping Project Report Principal Investigator: David E. Haddad Arizona State University ASU School of Earth and Space

More information

Generate Digital Elevation Models Using Laser Altimetry (LIDAR) Data

Generate Digital Elevation Models Using Laser Altimetry (LIDAR) Data Generate Digital Elevation Models Using Laser Altimetry (LIDAR) Data Literature Survey Christopher Weed October 2000 Abstract Laser altimetry (LIDAR) data must be processed to generate a digital elevation

More information

A METHOD OF MAP MATCHING FOR PERSONAL POSITIONING SYSTEMS

A METHOD OF MAP MATCHING FOR PERSONAL POSITIONING SYSTEMS The 21 st Asian Conference on Remote Sensing December 4-8, 2000 Taipei, TAIWA A METHOD OF MAP MATCHIG FOR PERSOAL POSITIOIG SSTEMS Kay KITAZAWA, usuke KOISHI, Ryosuke SHIBASAKI Ms., Center for Spatial

More information

QUICK START GUIDE. SOLO Forest

QUICK START GUIDE. SOLO Forest QUICK START GUIDE SOLO Forest Software Installation 1. For PC installation, run the.msi file. 2. For Mobile device installation, copy the.cab file onto the device 3. Run the.cab file Starting the Program

More information

Introduction Texture/Friction Measurement at Winnipeg International Airport Data Analysis Conclusions

Introduction Texture/Friction Measurement at Winnipeg International Airport Data Analysis Conclusions Texture/Friction Measurements and Analysis at Runway 13-31 of James Armstrong Richardson International Airport in Winnipeg Qingfan Liu, EIT, PhD candidate, University of Manitoba Ahmed Shalaby, PhD, P.

More information

LiDAR REMOTE SENSING DATA COLLECTION BISCUIT FIRE STUDY AREA, OREGON

LiDAR REMOTE SENSING DATA COLLECTION BISCUIT FIRE STUDY AREA, OREGON LiDAR REMOTE SENSING DATA COLLECTION BISCUIT FIRE STUDY AREA, OREGON Oblique view in the Biscuit Fire Study Area: Above Ground ESRI Grid (1-meter resolution) derived from all LiDAR points Submitted to:

More information

Relating Local Vision Measurements to Global Navigation Satellite Systems Using Waypoint Based Maps

Relating Local Vision Measurements to Global Navigation Satellite Systems Using Waypoint Based Maps Relating Local Vision Measurements to Global Navigation Satellite Systems Using Waypoint Based Maps John W. Allen Samuel Gin College of Engineering GPS and Vehicle Dynamics Lab Auburn University Auburn,

More information

Automatic DTM Extraction from Dense Raw LIDAR Data in Urban Areas

Automatic DTM Extraction from Dense Raw LIDAR Data in Urban Areas Automatic DTM Extraction from Dense Raw LIDAR Data in Urban Areas Nizar ABO AKEL, Ofer ZILBERSTEIN and Yerach DOYTSHER, Israel Key words: LIDAR, DSM, urban areas, DTM extraction. SUMMARY Although LIDAR

More information

Error Estimations in the Design of a Terrain Measurement System

Error Estimations in the Design of a Terrain Measurement System Error Estimations in the Design of a Terrain Measurement System Cameron S. Rainey Thesis submitted to the faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the

More information

Lab 4 Projectile Motion

Lab 4 Projectile Motion b Lab 4 Projectile Motion What You Need To Know: x = x v = v v o ox = v + v ox ox + at 1 t + at + a x FIGURE 1 Linear Motion Equations The Physics So far in lab you ve dealt with an object moving horizontally

More information

Phone: (603) Fax: (603) Table of Contents

Phone: (603) Fax: (603) Table of Contents Hydrologic and topographic controls on the distribution of organic carbon in forest Soils LIDAR Mapping Project Report Principal Investigator: Adam Finkelman Plumouth State University Plymouth State University,

More information

AC : MEASURING AND MODELING OF A 3-D ROAD SURFACE

AC : MEASURING AND MODELING OF A 3-D ROAD SURFACE AC 2008-2782: MEASURING AND MODELING OF A 3-D ROAD SURFACE Pramod Kumar, University of Louisiana at Lafayette Pavel Ikonomov, Western Michigan University Suren Dwivedi, University of Louisiana-Lafayette

More information

Alignment of Centimeter Scale Bathymetry using Six Degrees of Freedom

Alignment of Centimeter Scale Bathymetry using Six Degrees of Freedom Alignment of Centimeter Scale Bathymetry using Six Degrees of Freedom Ethan Slattery, University of California Santa Cruz Mentors: David Caress Summer 2018 Keywords: point-clouds, iterative closest point,

More information

Precision Hopping/Rolling Robotic Surface Probe Based on Tensegrity Structures. BEST Lab Seminar October 7 th, 2016 Brian Cera Edward Zhu

Precision Hopping/Rolling Robotic Surface Probe Based on Tensegrity Structures. BEST Lab Seminar October 7 th, 2016 Brian Cera Edward Zhu Precision Hopping/Rolling Robotic Surface Probe Based on Tensegrity Structures BEST Lab Seminar October 7 th, 2016 Brian Cera Edward Zhu 1 Research Objectives & Mission Requirements Secondary payload to

More information

Course Outline (1) #6 Data Acquisition for Built Environment. Fumio YAMAZAKI

Course Outline (1) #6 Data Acquisition for Built Environment. Fumio YAMAZAKI AT09.98 Applied GIS and Remote Sensing for Disaster Mitigation #6 Data Acquisition for Built Environment 9 October, 2002 Fumio YAMAZAKI yamazaki@ait.ac.th http://www.star.ait.ac.th/~yamazaki/ Course Outline

More information

Aided-inertial for GPS-denied Navigation and Mapping

Aided-inertial for GPS-denied Navigation and Mapping Aided-inertial for GPS-denied Navigation and Mapping Erik Lithopoulos Applanix Corporation 85 Leek Crescent, Richmond Ontario, Canada L4B 3B3 elithopoulos@applanix.com ABSTRACT This paper describes the

More information

3D laser road profiling for the automated measurement of road surface conditions and geometry.

3D laser road profiling for the automated measurement of road surface conditions and geometry. 3D laser road profiling for the automated measurement of road surface conditions and geometry. John Laurent 1, Jean François Hébert 1, Daniel Lefebvre 2, Yves Savard 3 1 Pavemetrics Systems inc., Canada

More information

Inertial Navigation Systems

Inertial Navigation Systems Inertial Navigation Systems Kiril Alexiev University of Pavia March 2017 1 /89 Navigation Estimate the position and orientation. Inertial navigation one of possible instruments. Newton law is used: F =

More information

Airborne Laser Survey Systems: Technology and Applications

Airborne Laser Survey Systems: Technology and Applications Abstract Airborne Laser Survey Systems: Technology and Applications Guangping HE Lambda Tech International, Inc. 2323B Blue Mound RD., Waukesha, WI-53186, USA Email: he@lambdatech.com As mapping products

More information

Critical Assessment of Automatic Traffic Sign Detection Using 3D LiDAR Point Cloud Data

Critical Assessment of Automatic Traffic Sign Detection Using 3D LiDAR Point Cloud Data 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 Critical Assessment of Automatic Traffic Sign Detection Using 3D LiDAR Point Cloud Data Chengbo Ai PhD Student School of Civil and Environmental Engineering

More information

Research on-board LIDAR point cloud data pretreatment

Research on-board LIDAR point cloud data pretreatment Acta Technica 62, No. 3B/2017, 1 16 c 2017 Institute of Thermomechanics CAS, v.v.i. Research on-board LIDAR point cloud data pretreatment Peng Cang 1, Zhenglin Yu 1, Bo Yu 2, 3 Abstract. In view of the

More information

CLASSIFICATION FOR ROADSIDE OBJECTS BASED ON SIMULATED LASER SCANNING

CLASSIFICATION FOR ROADSIDE OBJECTS BASED ON SIMULATED LASER SCANNING CLASSIFICATION FOR ROADSIDE OBJECTS BASED ON SIMULATED LASER SCANNING Kenta Fukano 1, and Hiroshi Masuda 2 1) Graduate student, Department of Intelligence Mechanical Engineering, The University of Electro-Communications,

More information

Lidar Sensors, Today & Tomorrow. Christian Sevcik RIEGL Laser Measurement Systems

Lidar Sensors, Today & Tomorrow. Christian Sevcik RIEGL Laser Measurement Systems Lidar Sensors, Today & Tomorrow Christian Sevcik RIEGL Laser Measurement Systems o o o o Online Waveform technology Stand alone operation no field computer required Remote control through wireless network

More information

Stochastic Road Shape Estimation, B. Southall & C. Taylor. Review by: Christopher Rasmussen

Stochastic Road Shape Estimation, B. Southall & C. Taylor. Review by: Christopher Rasmussen Stochastic Road Shape Estimation, B. Southall & C. Taylor Review by: Christopher Rasmussen September 26, 2002 Announcements Readings for next Tuesday: Chapter 14-14.4, 22-22.5 in Forsyth & Ponce Main Contributions

More information

Where s the Boss? : Monte Carlo Localization for an Autonomous Ground Vehicle using an Aerial Lidar Map

Where s the Boss? : Monte Carlo Localization for an Autonomous Ground Vehicle using an Aerial Lidar Map Where s the Boss? : Monte Carlo Localization for an Autonomous Ground Vehicle using an Aerial Lidar Map Sebastian Scherer, Young-Woo Seo, and Prasanna Velagapudi October 16, 2007 Robotics Institute Carnegie

More information