PATENT LIABILITY ANALYSIS. Daniel Barrett Sebastian Hening Sandunmalee Abeyratne Anthony Myers
|
|
- Jocelin Atkinson
- 5 years ago
- Views:
Transcription
1 PATENT LIABILITY ANALYSIS Autonomous Targeting Vehicle (ATV) Daniel Barrett Sebastian Hening Sandunmalee Abeyratne Anthony Myers
2 Autonomous wheeled vehicle with obstacle avoidance Two infrared range finder Single sonic range finder Vision assisted navigation MAIN FEATURES Webcam used to follow targets Allows user input for destination queue Method of dead-reckoning using Kalman filter Sensor data fusion Compass, Accelerometer, Wheel Encoders, GPS 2
3 Patent #1 Autonomous moving apparatus having obstacle avoidance function United States Patent Filing Date: October 11, 2001 Description: An autonomous moving apparatus that moves toward a destination while detecting and avoiding obstacles Horizontal plane scanning radar device to detect a position of an obstacle An obstacle sensor for detecting an obstacle in a space different from the scanning plane of the radar device. 3
4 Patent #1: Doctrine of Equivalents CLAIMS The non-scantype sensor is a set of supersonic sensors, arranged in a semicircular shaped area, or an optical sensor. ATV Onesonic range finder (on webcam) and two IR range finders (on front of vehicle). When obstacledetected, decrease speed. Same functionality. (Seems obvious) Vehicle is only allowed within certain distance of an object When obstacle detected, change direction until no obstacle is detected, then resume movement. Utilizes a specific-configuration detecting element. Same functionality. (Seems obvious) Does not detectspecific features of surrounding objects. 4
5 Robot system with vision sensor United States Patent Filing Date: October 5, 2005 Description: Patent #2 A robot system having a vision system that obtains image data of a working environment of the robot. A system consisting of a control section, imaging section, image processing section, vision controlling section, communication network. 5
6 Patent #2: Literal Infringement CLAIMS Robot system with said control / communication network. Robot has a vision controlling section that makes the imaging section obtain image data at predetermined time intervals. Perform position correctionbased on position data retrieved from imaging section. ATV Same functionality. (Seems obvious) Same functionality. Vision feature of ATV is used to track intended target,but does not indicate position. 6
7 Patent #3 Method and apparatus for reckoning position of moving robot United States Patent Filing Date: October 17, 2006 Description: A method and apparatus for reckoning a position of a moving robot using dead-reckoning and range sensing. The apparatus reckons its position by: Performing dead-reckoning to determine a variation state Determining absolute position by measuring its distance from a fixed object Predicting an optimized current position of the moving robot using said variation state and absolute position. 7
8 Patent #3: Doctrine of Equivalents CLAIMS Dead-reckoningis performed using an encoder and/or gyroscope. Fixedpositions are used in determining absolute position. A Kalman filter calculates the current state using the variation state and the absolute position,using information from an auxiliary sensor. Theauxiliary sensor is either a nearby obstacle sensor, a laser sensor, a distance sensor, or a camera. ATV Dead-reckoningis performed using two wheel encoders, accelerometer, and magnetometer. No fixed positions are used. GPS signal gives approximation of current location. Same functionality. Uses three range finders to determine relative distance to objects. 8
9 Google Maps Copyright Permission guidelines regarding specific use cases: All use of Google Maps and Google Earth and Content MUST provide attribution to Google and our suppliers. Content cannot be scraped or exported from Google Maps or Earth or be saved for offline use. The ATV uses a screenshot of Google Maps for the GUI This is in direction violation of the Google Copyright Licensing the image saved from the Google service is the only option 9
10 Questions? 10
Jo-Car2 Autonomous Mode. Path Planning (Cost Matrix Algorithm)
Chapter 8.2 Jo-Car2 Autonomous Mode Path Planning (Cost Matrix Algorithm) Introduction: In order to achieve its mission and reach the GPS goal safely; without crashing into obstacles or leaving the lane,
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 informationLocalization, 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 informationHomework 11: Reliability and Safety Analysis
ECE 477 Digital Systems Senior Design Project Rev 8/09 Homework 11: Reliability and Safety Analysis Team Code Name: ATV Group No. _3 Team Member Completing This Homework: Sebastian Hening E-mail Address
More informationOutline Sensors. EE Sensors. H.I. Bozma. Electric Electronic Engineering Bogazici University. December 13, 2017
Electric Electronic Engineering Bogazici University December 13, 2017 Absolute position measurement Outline Motion Odometry Inertial systems Environmental Tactile Proximity Sensing Ground-Based RF Beacons
More informationE80. Experimental Engineering. Lecture 9 Inertial Measurement
Lecture 9 Inertial Measurement http://www.volker-doormann.org/physics.htm Feb. 19, 2013 Christopher M. Clark Where is the rocket? Outline Sensors People Accelerometers Gyroscopes Representations State
More informationNAVIGATION SYSTEM OF AN OUTDOOR SERVICE ROBOT WITH HYBRID LOCOMOTION SYSTEM
NAVIGATION SYSTEM OF AN OUTDOOR SERVICE ROBOT WITH HYBRID LOCOMOTION SYSTEM Jorma Selkäinaho, Aarne Halme and Janne Paanajärvi Automation Technology Laboratory, Helsinki University of Technology, Espoo,
More informationNavigational Aids 1 st Semester/2007/TF 7:30 PM -9:00 PM
Glossary of Navigation Terms accelerometer. A device that senses inertial reaction to measure linear or angular acceleration. In its simplest form, it consists of a case-mounted spring and mass arrangement
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 information2002 Intelligent Ground Vehicle Competition Design Report. Grizzly Oakland University
2002 Intelligent Ground Vehicle Competition Design Report Grizzly Oakland University June 21, 2002 Submitted By: Matt Rizzo Brian Clark Brian Yurconis Jelena Nikolic I. ABSTRACT Grizzly is the product
More informationSTATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR THE NAMES OF THE PARTIES TO A JOINT RESEARCH AGREEMENT.
TITLE OF INVENTION. A distance measuring device using a method of spanning separately targeted endpoints. This application claims the benefit of U.S. Provisional Application No. 61/477,511, filed April
More informationProbabilistic Robotics
Probabilistic Robotics Probabilistic Motion and Sensor Models Some slides adopted from: Wolfram Burgard, Cyrill Stachniss, Maren Bennewitz, Kai Arras and Probabilistic Robotics Book SA-1 Sensors for Mobile
More informationMTRX4700: Experimental Robotics
Stefan B. Williams April, 2013 MTR4700: Experimental Robotics Assignment 3 Note: This assignment contributes 10% towards your final mark. This assignment is due on Friday, May 10 th during Week 9 before
More informationSLAM: Robotic Simultaneous Location and Mapping
SLAM: Robotic Simultaneous Location and Mapping William Regli Department of Computer Science (and Departments of ECE and MEM) Drexel University Acknowledgments to Sebastian Thrun & others SLAM Lecture
More informationCSE-571 Robotics. Sensors for Mobile Robots. Beam-based Sensor Model. Proximity Sensors. Probabilistic Sensor Models. Beam-based Scan-based Landmarks
Sensors for Mobile Robots CSE-57 Robotics Probabilistic Sensor Models Beam-based Scan-based Landmarks Contact sensors: Bumpers Internal sensors Accelerometers (spring-mounted masses) Gyroscopes (spinning
More informationIntelligent Outdoor Navigation of a Mobile Robot Platform Using a Low Cost High Precision RTK-GPS and Obstacle Avoidance System
Intelligent Outdoor Navigation of a Mobile Robot Platform Using a Low Cost High Precision RTK-GPS and Obstacle Avoidance System Under supervision of: Prof. Dr. -Ing. Klaus-Dieter Kuhnert Dipl.-Inform.
More informationTomTom Innovation. Hans Aerts VP Software Development Business Unit Automotive November 2015
TomTom Innovation Hans Aerts VP Software Development Business Unit Automotive November 2015 Empower Movement Simplify complex technology From A to BE Innovative solutions Maps Consumer Connect people and
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 informationSensor technology for mobile robots
Laser application, vision application, sonar application and sensor fusion (6wasserf@informatik.uni-hamburg.de) Outline Introduction Mobile robots perception Definitions Sensor classification Sensor Performance
More informationOptical Sensors: Key Technology for the Autonomous Car
Optical Sensors: Key Technology for the Autonomous Car Rajeev Thakur, P.E., Product Marketing Manager, Infrared Business Unit, Osram Opto Semiconductors Autonomously driven cars will combine a variety
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 informationCamera 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 informationRobotics. Chapter 25. Chapter 25 1
Robotics Chapter 25 Chapter 25 1 Outline Robots, Effectors, and Sensors Localization and Mapping Motion Planning Chapter 25 2 Mobile Robots Chapter 25 3 Manipulators P R R R R R Configuration of robot
More informationBuild and Test Plan: IGV Team
Build and Test Plan: IGV Team 2/6/2008 William Burke Donaldson Diego Gonzales David Mustain Ray Laser Range Finder Week 3 Jan 29 The laser range finder will be set-up in the lab and connected to the computer
More informationUNIVERSITY OF NORTH CAROLINA AT CHARLOTTE
UNIVERSITY OF NORTH CAROLINA AT CHARLOTTE Department of Electrical and Computer Engineering ECGR 4161/5196 Introduction to Robotics Experiment No. 5 A* Path Planning Overview: The purpose of this experiment
More informationBasics of Localization, Mapping and SLAM. Jari Saarinen Aalto University Department of Automation and systems Technology
Basics of Localization, Mapping and SLAM Jari Saarinen Aalto University Department of Automation and systems Technology Content Introduction to Problem (s) Localization A few basic equations Dead Reckoning
More informationVehicle 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 informationRange Imaging Through Triangulation. Range Imaging Through Triangulation. Range Imaging Through Triangulation. Range Imaging Through Triangulation
Obviously, this is a very slow process and not suitable for dynamic scenes. To speed things up, we can use a laser that projects a vertical line of light onto the scene. This laser rotates around its vertical
More informationIMU and Encoders. Team project Robocon 2016
IMU and Encoders Team project Robocon 2016 Harsh Sinha, 14265, harshsin@iitk.ac.in Deepak Gangwar, 14208, dgangwar@iitk.ac.in Swati Gupta, 14742, swatig@iitk.ac.in March 17 th 2016 IMU and Encoders Module
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 informationProc. 14th Int. Conf. on Intelligent Autonomous Systems (IAS-14), 2016
Proc. 14th Int. Conf. on Intelligent Autonomous Systems (IAS-14), 2016 Outdoor Robot Navigation Based on View-based Global Localization and Local Navigation Yohei Inoue, Jun Miura, and Shuji Oishi Department
More informationFire Bird V Insect - Nex Robotics
Fire Bird V Insect is a small six legged robot. It has three pair of legs driven by one servo each. Robot can navigate itself using Sharp IR range sensors. It can be controlled wirelessly using ZigBee
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 informationHomework 13: User Manual
Homework 13: User Manual Team Code Name: Autonomous Targeting Vehicle Group No. 3 User Manual Outline: Brief (marketing-style) product description Product illustration annotated with callouts for each
More informationSolid State LiDAR for Ubiquitous 3D Sensing
April 6, 2016 Solid State LiDAR for Ubiquitous 3D Sensing Louay Eldada, Ph.D. CEO, Co-founder Quanergy Systems New Paradigm in 3D Sensing Disruptive Technologies: Solid State 3D LiDAR sensors Embedded
More informationMULTI-MODAL MAPPING. Robotics Day, 31 Mar Frank Mascarich, Shehryar Khattak, Tung Dang
MULTI-MODAL MAPPING Robotics Day, 31 Mar 2017 Frank Mascarich, Shehryar Khattak, Tung Dang Application-Specific Sensors Cameras TOF Cameras PERCEPTION LiDAR IMU Localization Mapping Autonomy Robotic Perception
More informationAnnouncements. CS 188: Artificial Intelligence Spring Advanced Applications. Robot folds towels. Robotic Control Tasks
CS 188: Artificial Intelligence Spring 2011 Advanced Applications: Robotics Announcements Practice Final Out (optional) Similar extra credit system as practice midterm Contest (optional): Tomorrow night
More informationCS 188: Artificial Intelligence Spring Announcements
CS 188: Artificial Intelligence Spring 2011 Advanced Applications: Robotics Pieter Abbeel UC Berkeley A few slides from Sebastian Thrun, Dan Klein 1 Announcements Practice Final Out (optional) Similar
More informationOld View of Perception vs. New View
Old View of Perception vs. New View Traditional ( old view ) approach: Perception considered in isolation (i.e., disembodied) Perception as king (e.g., computer vision is the problem) Universal reconstruction
More informationMotion 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 informationTowards the Consumerization of Smart Sensors
Towards the Consumerization of Smart Sensors Roberto De Nuccio Business Development Manager MEMS, Sensors and High-Performance Analog Division STMicroelectronics Micro-Electro-Mechanical Systems (MEMS)
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 informationHybrid Indoor Positioning and Directional Querying on a Ubiquitous Mobile Device
Dublin Institute of Technology ARROW@DIT Conference papers Digital Media Centre 2009-09-01 Hybrid Indoor Positioning and Directional Querying on a Ubiquitous Mobile Device Viacheslav Filonenko Dublin Institute
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 informationIndoor Mobile Robot Navigation and Obstacle Avoidance Using a 3D Camera and Laser Scanner
AARMS Vol. 15, No. 1 (2016) 51 59. Indoor Mobile Robot Navigation and Obstacle Avoidance Using a 3D Camera and Laser Scanner Peter KUCSERA 1 Thanks to the developing sensor technology in mobile robot navigation
More informationAutonomous Vehicle Navigation Using Stereoscopic Imaging
Autonomous Vehicle Navigation Using Stereoscopic Imaging Project Proposal By: Beach Wlaznik Advisors: Dr. Huggins Dr. Stewart December 7, 2006 I. Introduction The objective of the Autonomous Vehicle Navigation
More informationRobot Localization based on Geo-referenced Images and G raphic Methods
Robot Localization based on Geo-referenced Images and G raphic Methods Sid Ahmed Berrabah Mechanical Department, Royal Military School, Belgium, sidahmed.berrabah@rma.ac.be Janusz Bedkowski, Łukasz Lubasiński,
More informationAutonomous Navigation for Flying Robots
Computer Vision Group Prof. Daniel Cremers Autonomous Navigation for Flying Robots Lecture 3.2: Sensors Jürgen Sturm Technische Universität München Sensors IMUs (inertial measurement units) Accelerometers
More informationJames Van Rens CEO Riegl USA, Inc. Mining Industry and UAV s combined with LIDAR Commercial UAV Las Vegas October 2015 James Van Rens CEO Riegl USA
James Van Rens CEO Riegl USA, Inc. Mining Industry and UAV s combined with LIDAR Commercial UAV Las Vegas October 2015 James Van Rens CEO Riegl USA COST EFFECIENCY CONTINUUM LIDAR and IMU Partnership Technology
More informationGPS denied Navigation Solutions
GPS denied Navigation Solutions Krishnraj Singh Gaur and Mangal Kothari ksgaur@iitk.ac.in, mangal@iitk.ac.in https://www.iitk.ac.in/aero/mangal/ Intelligent Guidance and Control Laboratory Indian Institute
More informationEpipolar geometry-based ego-localization using an in-vehicle monocular camera
Epipolar geometry-based ego-localization using an in-vehicle monocular camera Haruya Kyutoku 1, Yasutomo Kawanishi 1, Daisuke Deguchi 1, Ichiro Ide 1, Hiroshi Murase 1 1 : Nagoya University, Japan E-mail:
More informationFAB verses tradition camera-based motion capture systems
FAB verses tradition camera-based motion capture systems The advent of micromachined inertial sensors, such as rate gyroscopes and accelerometers, has made new navigation and tracking technologies possible.
More informationSupplier Business Opportunities on ADAS and Autonomous Driving Technologies
AUTOMOTIVE Supplier Business Opportunities on ADAS and Autonomous Driving Technologies 19 October 2016 Tokyo, Japan Masanori Matsubara, Senior Analyst, +81 3 6262 1734, Masanori.Matsubara@ihsmarkit.com
More informationData Association for SLAM
CALIFORNIA INSTITUTE OF TECHNOLOGY ME/CS 132a, Winter 2011 Lab #2 Due: Mar 10th, 2011 Part I Data Association for SLAM 1 Introduction For this part, you will experiment with a simulation of an EKF SLAM
More informationA Vision and Differential Steering System for a Mobile Robot Platform Abujawad Rafid Siddiqui
Master Thesis Computer Science Thesis no: MCS-2010-22 May 2010 A Vision and Differential Steering System for a Mobile Robot Platform Abujawad Rafid Siddiqui School School of Computing of Blekinge Institute
More informationCS4495/6495 Introduction to Computer Vision
CS4495/6495 Introduction to Computer Vision 9C-L1 3D perception Some slides by Kelsey Hawkins Motivation Why do animals, people & robots need vision? To detect and recognize objects/landmarks Is that a
More informationW4. 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 informationCS283: Robotics Fall 2016: Software
CS283: Robotics Fall 2016: Software Sören Schwertfeger / 师泽仁 ShanghaiTech University Mobile Robotics ShanghaiTech University - SIST - 18.09.2016 2 Review Definition Robot: A machine capable of performing
More informationSatellite 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 informationAttack Resilient State Estimation for Vehicular Systems
December 15 th 2013. T-SET Final Report Attack Resilient State Estimation for Vehicular Systems Nicola Bezzo (nicbezzo@seas.upenn.edu) Prof. Insup Lee (lee@cis.upenn.edu) PRECISE Center University of Pennsylvania
More informationME 597/747 Autonomous Mobile Robots. Mid Term Exam. Duration: 2 hour Total Marks: 100
ME 597/747 Autonomous Mobile Robots Mid Term Exam Duration: 2 hour Total Marks: 100 Instructions: Read the exam carefully before starting. Equations are at the back, but they are NOT necessarily valid
More informationGuidance, Navigation and Control issues for Hayabusa follow-on missions F. Terui, N. Ogawa, O. Mori JAXA (Japan Aerospace Exploration Agency )
18-20th May 2009 Guidance, Navigation and Control issues for Hayabusa follow-on missions F. Terui, N. Ogawa, O. Mori JAXA (Japan Aerospace Exploration Agency ) Lessons and Learned & heritage from Proximity
More informationUnderstand various definitions related to sensing/perception. Understand variety of sensing techniques
Sensing/Perception Objectives Understand various definitions related to sensing/perception Understand variety of sensing techniques Understand challenges of sensing and perception in robotics Motivations
More informationPrecision Roadway Feature Mapping Jay A. Farrell, University of California-Riverside James A. Arnold, Department of Transportation
Precision Roadway Feature Mapping Jay A. Farrell, University of California-Riverside James A. Arnold, Department of Transportation February 26, 2013 ESRA Fed. GIS Outline: Big picture: Positioning and
More informationIndoor navigation using smartphones. Chris Hide IESSG, University of Nottingham, UK
Indoor navigation using smartphones Chris Hide IESSG, University of Nottingham, UK Overview Smartphones Available sensors Current positioning methods Positioning research at IESSG 1. Wi-Fi fingerprinting
More informationCamera and Inertial Sensor Fusion
January 6, 2018 For First Robotics 2018 Camera and Inertial Sensor Fusion David Zhang david.chao.zhang@gmail.com Version 4.1 1 My Background Ph.D. of Physics - Penn State Univ. Research scientist at SRI
More informationLow Cost solution for Pose Estimation of Quadrotor
Low Cost solution for Pose Estimation of Quadrotor mangal@iitk.ac.in https://www.iitk.ac.in/aero/mangal/ Intelligent Guidance and Control Laboratory Indian Institute of Technology, Kanpur Mangal Kothari
More informationSensory 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 informationLocalization algorithm using a virtual label for a mobile robot in indoor and outdoor environments
Artif Life Robotics (2011) 16:361 365 ISAROB 2011 DOI 10.1007/s10015-011-0951-7 ORIGINAL ARTICLE Ki Ho Yu Min Cheol Lee Jung Hun Heo Youn Geun Moon Localization algorithm using a virtual label for a mobile
More information12th Intelligent Ground Vehicle Competition
12th Intelligent Ground Vehicle Competition Design Competition Written Report AMIGO2004 HOSEI UNIVERSITY Signed Date Watanabe Laboratory Team System and Control Engineering Department Faculty of Engineering
More informationRobotics. Haslum COMP3620/6320
Robotics P@trik Haslum COMP3620/6320 Introduction Robotics Industrial Automation * Repetitive manipulation tasks (assembly, etc). * Well-known, controlled environment. * High-power, high-precision, very
More information3D Terrain Sensing System using Laser Range Finder with Arm-Type Movable Unit
3D Terrain Sensing System using Laser Range Finder with Arm-Type Movable Unit 9 Toyomi Fujita and Yuya Kondo Tohoku Institute of Technology Japan 1. Introduction A 3D configuration and terrain sensing
More informationHigh Accuracy Navigation Using Laser Range Sensors in Outdoor Applications
Proceedings of the 2000 IEEE International Conference on Robotics & Automation San Francisco, CA April 2000 High Accuracy Navigation Using Laser Range Sensors in Outdoor Applications Jose Guivant, Eduardo
More informationUnmanned Vehicle Technology Researches for Outdoor Environments. *Ju-Jang Lee 1)
Keynote Paper Unmanned Vehicle Technology Researches for Outdoor Environments *Ju-Jang Lee 1) 1) Department of Electrical Engineering, KAIST, Daejeon 305-701, Korea 1) jjlee@ee.kaist.ac.kr ABSTRACT The
More informationLecture: Autonomous micro aerial vehicles
Lecture: Autonomous micro aerial vehicles Friedrich Fraundorfer Remote Sensing Technology TU München 1/41 Autonomous operation@eth Zürich Start 2/41 Autonomous operation@eth Zürich 3/41 Outline MAV system
More informationUsing infrared proximity sensors for close 2D localization and object size recognition. Richard Berglind Neonode
Using infrared proximity sensors for close 2D localization and object size recognition Richard Berglind Neonode Outline Overview of sensor types IR proximity sensors and their drawbacks Principles of a
More informationState Estimation for Continuous-Time Systems with Perspective Outputs from Discrete Noisy Time-Delayed Measurements
State Estimation for Continuous-Time Systems with Perspective Outputs from Discrete Noisy Time-Delayed Measurements António Pedro Aguiar aguiar@ece.ucsb.edu João Pedro Hespanha hespanha@ece.ucsb.edu Dept.
More informationExploration of an Indoor-Environment by an Autonomous Mobile Robot
IROS '94 September 12-16, 1994 Munich, Germany page 1 of 7 Exploration of an Indoor-Environment by an Autonomous Mobile Robot Thomas Edlinger edlinger@informatik.uni-kl.de Ewald von Puttkamer puttkam@informatik.uni-kl.de
More informationAutonomous navigation in industrial cluttered environments using embedded stereo-vision
Autonomous navigation in industrial cluttered environments using embedded stereo-vision Julien Marzat ONERA Palaiseau Aerial Robotics workshop, Paris, 8-9 March 2017 1 Copernic Lab (ONERA Palaiseau) Research
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 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 informationDesign Report prepared by: Shawn Brovold Gregory Rupp Eric Li Nathan Carlson. Faculty Advisor: Max Donath
13 th Annual Intelligent Ground Vehicle Competition 2005 Design Report Design Report prepared by: Shawn Brovold Gregory Rupp Eric Li Nathan Carlson Faculty Advisor: Max Donath Faculty Certification I,
More informationOFERTA O120410PA CURRENT DATE 10/04//2012 VALID UNTIL 10/05/2012 SUMMIT XL
OFERTA O120410PA CURRENT DATE 10/04//2012 VALID UNTIL 10/05/2012 SUMMIT XL CLIENT CLIENT: Gaitech REPRESENTANT: Andrew Pether MAIL: andyroojp@hotmail.com PRODUCT Introduction The SUMMIT XL has skid-steering
More informationHuman Detection. A state-of-the-art survey. Mohammad Dorgham. University of Hamburg
Human Detection A state-of-the-art survey Mohammad Dorgham University of Hamburg Presentation outline Motivation Applications Overview of approaches (categorized) Approaches details References Motivation
More informationThomas Bräunl EMBEDDED ROBOTICS. Mobile Robot Design and Applications with Embedded Systems. Second Edition. With 233 Figures and 24 Tables.
Thomas Bräunl EMBEDDED ROBOTICS Mobile Robot Design and Applications with Embedded Systems Second Edition With 233 Figures and 24 Tables Springer CONTENTS PART I: EMBEDDED SYSTEMS 1 Robots and Controllers
More informationCollaboration is encouraged among small groups (e.g., 2-3 students).
Assignments Policies You must typeset, choices: Word (very easy to type math expressions) Latex (very easy to type math expressions) Google doc Plain text + math formula Your favorite text/doc editor Submit
More informationAnalysis of Obstacle Detection Technologies used in Mobile Robots
ISSN (Online) : 2319-8753 ISSN (Print) : 2347-6710 International Journal of Innovative Research in Science, Engineering and Technology Volume 3, Special Issue 3, March 2014 2014 International Conference
More informationMapping Contoured Terrain Using SLAM with a Radio- Controlled Helicopter Platform. Project Proposal. Cognitive Robotics, Spring 2005
Mapping Contoured Terrain Using SLAM with a Radio- Controlled Helicopter Platform Project Proposal Cognitive Robotics, Spring 2005 Kaijen Hsiao Henry de Plinval Jason Miller Introduction In the context
More informationSatellite/Inertial Navigation and Positioning System (SINAPS)
Satellite/Inertial Navigation and Positioning System (SINAPS) Functional Requirements List and Performance Specifications by Daniel Monroe, Luke Pfister Advised By Drs. In Soo Ahn and Yufeng Lu ECE Department
More informationA USABILITY EVALUATION OF A 3D MAP DISPLAY FOR PEDESTRIAN NAVIGATION
September 29 th, 2018 A USABILITY EVALUATION OF A 3D MAP DISPLAY FOR PEDESTRIAN NAVIGATION Key words: Pedestrian Navigation, LOD 1, 3D, 2D, Usability Department of Geodetic Engineering, Universitas Gadjah
More informationFIDUCIAL BASED POSE ESTIMATION ADEWOLE AYOADE ALEX YEARSLEY
FIDUCIAL BASED POSE ESTIMATION ADEWOLE AYOADE ALEX YEARSLEY OVERVIEW Objective Motivation Previous Work Methods Target Recognition Target Identification Pose Estimation Testing Results Demonstration Conclusion
More informationMoveaTV PC Evaluation Kit Quick Start Guide
MoveaTV PC Evaluation Kit Quick Start Guide PACKAGE CONTENT 1 Remote 1 USB Dongle 3 AAA Batteries 1 USB Stick Containing MoveaTV Application Installer Motion button and left and right click Double click
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 informationCalibration of a rotating multi-beam Lidar
The 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems October 18-22, 2010, Taipei, Taiwan Calibration of a rotating multi-beam Lidar Naveed Muhammad 1,2 and Simon Lacroix 1,2 Abstract
More informationOverview. EECS 124, UC Berkeley, Spring 2008 Lecture 23: Localization and Mapping. Statistical Models
Introduction ti to Embedded dsystems EECS 124, UC Berkeley, Spring 2008 Lecture 23: Localization and Mapping Gabe Hoffmann Ph.D. Candidate, Aero/Astro Engineering Stanford University Statistical Models
More informationPhone: Fax: World Headquarters: 180 Adams Ave. Hauppauge NY Rev.
AVENTURA THERMAL IMAGING INTELLIGENT CAMERA SYSTEMS Model CAM-TI Series CAM-TIVL Series CAM-TIVL-MP Series Photo THERMAL CAMERA Style Standalone Thermal Imaging Camera Thermal Imaging / Visible-Light Camera
More informationSensor-fusion Demo Documentation
Sensor-fusion Demo Documentation Release 1.2 Alexander Pacha Aug 13, 2018 Contents: 1 Euler Angles 3 2 Installation 5 3 Contribute 7 4 License 9 i ii Sensor-fusion Demo Documentation, Release 1.2 This
More information9th Intelligent Ground Vehicle Competition. Design Competition Written Report. Design Change Report AMIGO
9th Intelligent Ground Vehicle Competition Design Competition Written Report Design Change Report AMIGO AMIGO means the friends who will join to the IGV Competition. Watanabe Laboratory Team System Control
More informationComputationally Efficient Visual-inertial Sensor Fusion for GPS-denied Navigation on a Small Quadrotor
Computationally Efficient Visual-inertial Sensor Fusion for GPS-denied Navigation on a Small Quadrotor Chang Liu & Stephen D. Prior Faculty of Engineering and the Environment, University of Southampton,
More information