Critical Design Review: Dead Reckoning System for Mobile Robots Lee FithianSteven Parkinson Ajay JosephSaba Rizvi.

Slides:



Advertisements
Similar presentations
Simulation Examples in EXCEL Montana Going Green 2010.
Advertisements

Understanding Electrical TransmissionDemonstration D1 A Guide to the National Grid Transmission Model Demonstration D1 Power losses in transmission.
Making Movement Easy for the Visually Impaired. As per the survey conducted on visually disabled people it was discovered that the white cane is an integral.
Autonomous Mapping Robot Jason Ogasian Jonathan Hayden Hiroshi Mita Worcester Polytechnic Institute Department of Electrical and Computer Engineering Advisor:
1 Sensors, Actuators, Signals, and Computers Part D Ping Hsu, Winncy Du, Ken Youssefi.
The Pied Pipers Alyssa Visitacion Ken Shum Joanne Flores.
Final Demonstration: Dead Reckoning System for Mobile Robots Lee FithianSteven Parkinson Ajay JosephSaba Rizvi.
A.G.I.L.E Team Members: Brad Ramsey Derek Rodriguez Dane Wielgopolan Project Managers: Dr. Joel Schipper Dr. James Irwin Autonomously Guided Intelligent.
GPSBot08 System Overview.
Dead Reckoning System for Mobile Robots Lee FithianSteven Parkinson Ajay JosephSaba Rizvi.
224 Final Project Kendra Armstrong - Nick Eccles - Cary Maguire - Alex Taam - Paul Williams.
Team MASTers™ Craig Lalumiere David Cobler Michael White.
Preliminary Design Review
Field Navigational GPS Robot Final Presentation & Review Chris Foley, Kris Horn, Richard Neil Pittman, Michael Willis.
ME 224 Final Presentation Fall 2005 Joni Stegeman Ingrid Lin Giovanni Wuisan Patrick Luckow Brent Willson.
Integrating POMDP and RL for a Two Layer Simulated Robot Architecture Presented by Alp Sardağ.
GPS Robot Navigation Critical Design Review Chris Foley, Kris Horn, Richard Neil Pittman, Michael Willis.
P09204 Robotic Platform (RP1)‏ Project Overview Robotic Platform for 1kg Loads (2 nd Generation)‏ One or More scalable Motor Modules Controller System.
The Enforcer Laura Celentano Glenn Ramsey Michael Szalkowski.
EIGHTH GRADE ROBOTICS KITTATINNY REGIONAL HIGH SCHOOL MR. SHEA Introduction to Robotics Day4.
University of Pennsylvania Department of Electrical and Systems Engineering ABSTRACT: Quantifying and measuring certain aspects of a golf swing is a helpful.
Design Review: RoboSiM Robotic Surveillance in Motion
Advanced Robotics – “Wobble” Milestone Presentation Patrick Barnes Jin Sub Lee Arild Hjelle Spring 2004.
Use of Multimedia in Engineering. Mechatronics engineering is based on the combination from three basic engineering field that is mechaninal, electronics.
Controller, Sensors and Motors Ding Ke Tutorial 1, UGB 230N.
Electrical and Computer Engineering Personal Head-Up Display Ivan Bercovich Radu-Andrei Ivan Jeff Little Felipe Vilas-Boas Faculty: Dr. Tilman Wolf Midway.
June 12, 2001 Jeong-Su Han An Autonomous Vehicle for People with Motor Disabilities by G. Bourhis, O.Horn, O.Habert and A. Pruski Paper Review.
To control the movement of a manual wheelchair by means of human voice for paralyzed patients. AIM:
USING SAT-BASED CRAIG INTERPOLATION TO ENLARGE CLOCK GATING FUNCTIONS Ting-Hao Lin, Chung-Yang (Ric) Huang Graduate Institute of Electrical Engineering,
Digital data acquisition1 Measuring ? „Wer misst, misst Mist.“ numeric result Sensing, Signal Processing Evaluation Physical/Chemical Property Physical/Chemical.
E-LABORATORY PRACTICAL TEACHING FOR APPLIED ENGINEERING SCIENCES W O R K S H O P University of Oradea, Romania February 6, 2012 G E N E R A L P R E S E.
Abstract Design Considerations and Future Plans In this project we focus on integrating sensors into a small electrical vehicle to enable it to navigate.
ECE 4006 Project Proposal and Presentation Group Members – John Sellers - Doug Messick - Kelvin Bunn - Sean James Group Name: Altera NIOS Robot Group School.
Team Spot A Cooperative Robotics Problem A Robotics Academy Project: Laurel Hesch Emily Mower Addie Sutphen.
Micro-Mouse By Mohamad Samhat Narciso Lumbreras Hasan Almatrouk.
Sensing self motion Key points: Why robots need self-sensing Sensors for proprioception in biological systems in robot systems Position sensing Velocity.
A Framework for use in SLAM algorithms Principle Investigator: Shaun Egan Supervisor: Dr. Karen Bradshaw.
INEMO™ Demonstration Kit DOF (Degrees of Freedom) platform  The STEVAL-MKI062V2 combines accelerometers, gyroscopes and magnetometers with pressure.
Level 2 Unit 5 Electrical and Electronic Circuits and Systems Engineering Diploma Level 2 Unit 5 Electrical and Electronic Circuits and Systems Electronic.
MIR – Mobile Intelligence Robot By Jason Abbett and Devon Berry.
Representing Numerical Data Analog Any signal that varies continuously over time Mechanical Pneumatic Hydraulic Electrical Digital Quantities are represented.
Sensor Pack Binary Tone Generator Rabbit Processor IMUGPS Receiver Xbee Radio Modem Data Sink GPS Satellites Handset for Binary Tone Generator Operator:
Scientific Method A blueprint for experiment success.
3D Printed Robotic Glove Open source design for use in rehabilitation therapy for individuals with limited hand motor function. Retrains the muscles and.
Status Report #2 Autonomous Lawnmower Team 5 April Fowler Jose Manzanares Ranjith Raghunath Christopher Gerhardt 5 Feb 07 To design and implement an autonomous.
Team 18: Humble Hubble The proposed project is a self-aiming telescope. This telescope will interface with a host device to populate a list of celestial.
Ali Alkuwari Patrick SwannJad FarahMarcus SchafferKorhan Demirkaya Long QuyDenden TekesteNgoc MaiSteven Weaver.
1 Motion Fuzzy Controller Structure(1/7) In this part, we start design the fuzzy logic controller aimed at producing the velocities of the robot right.
Head movements based control of an intelligent wheelchair in an indoor environment E.J. Rechy-Ramirez and H. Hu University of Essex 24 April 2012 Colchester,
1 ©2006 INSciTE Common Blocks. 2 ©2006 INSciTE Common Blocks Common blocks are full featured actions Like English statements Move Wait for an action Display.
Presented by SUNIL A.G..  Introduction to embedded systems.  Design of embedded system in general  Amount of hardware needed.  Optimizing power dissipation.
Sensor Fusion Donald Heer 11/10/10. The Questions Can two things happen at the ‘same’ time? Can the same thing be observed ‘identically’ by two different.
Maze Twinbots Group 28 Uyen Nguyen – EE Ly Nguyen – EE Luke Ireland - EE.
Ali Alkuwari Patrick SwannJad FarahMarcus SchafferKorhan Demirkaya Long QuyDenden TekesteNgoc MaiSteven Weaver.
Fluid Power Control.
Wireless charging of mobile phones using microwaves
Localization Life in the Atacama 2004 Science & Technology Workshop January 6-7, 2005 Daniel Villa Carnegie Mellon Matthew Deans QSS/NASA Ames.
VEX Cortex Video Trainer using ROBOTC
VEX IQ Mix & Match Curriculum
AIM: To control the movement of a manual wheelchair by means of human voice for paralyzed patients.
Creating Robotic Platforms
Product Evaluation & Quality Improvement
Product Evaluation & Quality Improvement

How can we make a robot more energy efficient?
Autonomous Targeting Vehicle (ATV)
Image Acquisition and Processing of Remotely Sensed Data
Counter Integrated Circuits (I.C.s)
Presentation transcript:

Critical Design Review: Dead Reckoning System for Mobile Robots Lee FithianSteven Parkinson Ajay JosephSaba Rizvi

Problem Statement  Use a mobile robot and develop a synthesized navigation algorithm.  We will integrate various sensors.

Modules I. Sensor Interface I. Produces output from the electrical inputs it receives; x-, y-distance traveled & heading II. Navigation I. Allows for different methods to be used regardless of input and output needs III. Movement I. Controls motors; can be modified if motors are changed

Accelerometer

 Created an algorithm that changes electrical output into position data.  A(g) = (T1/T2 – 0.5)/12.5%  Pos = (A(g) * t^2)/2  Pos = Pos Start + Pos New

Shaft encoder

Shaft Encoder  D = (Left D + Right D) / 2  Θ = (Left D – Right D) / b  X = D * cos(Θ)  Y = D * sin(Θ)

Gyroscope

Compass

Merging Data  Average positions calculated from sensors  Weighted average of positions calculated from sensors  Use sensors calculations for certain tasks and scale the results

Problems  Basic Misunderstanding of problem statement  OOPic limitations  Counter usage, frequency generator  Delay of parts  Building robot vs. assembly of robot

Changes  Added sensors  Compass, gyroscope  Upgraded OOPic  Memory, Faster uC  Added protoboard  Switched to rechargeable batteries  Integrated sensor for position calculation

Circuit Diagram

Conclusion  Construction  Mark III based robot with shaft encoders, accelerometers, compass, gyroscope  Validation to ensure systems work at a basic level  Experimentation  Use dead reckoning navigation in trials.  Record trials on butcher paper  Analysis  Numerical analysis of accuracy of navigation method.