Using inertial navigation systems (INS) to navigate

Slides:



Advertisements
Similar presentations
1 st MEMS Commercial Tuning Fork Gyroscope Draper Labs M. Weinberg, J. Bernstein, S. Cho, A. T. King, A. Kourepenis, P. Ward, and J. Sohn, A micromachined.
Advertisements

Andrew Hoogendam Dave Moelker Anthony Boorsma Danny VanderSpek.
MicroCART Micro processor C ontrolled A erial R obotics T eam Abstract MicroCART is a group of EE/CprE students tasked with developing an autonomous helicopter.
Pima Community College 4/12/14 Team Members Nick Patzke Gustavo Guerrero Nick Morris UAV Design, Manufacture and Applications Arizona NASA Space Grant.
Using inertial navigation systems (INS) to navigate
Unmanned Aerial Vehicles Presentation. Customization for each client Each order is specifically designed to meet each clients’ aerial needs. On-board.
INS : State of the art Yves PATUREL. 2 INS : noise on the sensors For inertial sensors, one typical way of measuring noise is the draw the Allan variance.
ROBOT LOCALISATION & MAPPING: MAPPING & LIDAR By James Mead.
© Copyright 2011 MicroStrain Inc. High Performance Miniature Inertial Measurement Systems MicroStrain Inc Mike Robinson
Reinforcement Learning in Quadrotor Helicopters
Parth Kumar ME5643: Mechatronics UAV ATTITUDE AND HEADING HOLD SYSTEM.
Inertial Measurement Unit “IMU” (Analog Devices ADIS16350) - Tri-axis gyroscope ± 75°/s, ± 150°/s, ± 300°/s settings - Tri-axis accelerometer ± 10 g measurement.
P09233 Flight Parameter Measurements Michael Skube & James Hunt P09233
1 Autonomous Controller Design for Unmanned Aerial Vehicles using Multi-objective Genetic Programming Choong K. Oh and Gregory J. Barlow U.S. Naval Research.
1 Incremental Evolution of Autonomous Controllers for Unmanned Aerial Vehicles using Multi-objective Genetic Programming Gregory J. Barlow, Choong K. Oh,
Design of Autonomous Navigation Controllers for Unmanned Aerial Vehicles using Multi-objective Genetic Programming Gregory J. Barlow March 19, 2004.
1 Autonomous Controller Design for Unmanned Aerial Vehicles using Multi-objective Genetic Programming Gregory J. Barlow North Carolina State University.
POLI di MI tecnicolano VISION-AUGMENTED INERTIAL NAVIGATION BY SENSOR FUSION FOR AN AUTONOMOUS ROTORCRAFT VEHICLE C.L. Bottasso, D. Leonello Politecnico.
EDGE™ MAV Control System - P09122 Final Project Review Erik Bellandi – Project Manager Ben Wager – Lead Engineer Garrett Argenna – Mechanical Engineering.
1. The Promise of MEMS to LBS and Navigation Applications Dr. Naser El-Shiemy, CEO Trusted Positioning Inc. 2.
An INS/GPS Navigation System with MEMS Inertial Sensors for Small Unmanned Aerial Vehicles Masaru Naruoka The University of Tokyo 1.Introduction.
Unmanned aerial systems, what they are and what is available? Professor Sandor M Veres University of Sheffield.
Development of a Fully Autonomous Micro Aerial Vehicle for Ground Traffic Surveillance Aerospace Systems, University of Braunschweig.
Sérgio Ronaldo Barros dos Santos (ITA-Brazil)
Automated Aerial Sturgeon RF Tag Tracking Platform 30cc Bravata ARF QB kit (Airframe) Tail Frame Modification Cargo Bay development 3DR Pixhawk (Autopilot)
IMPROVE THE INNOVATION Today: High Performance Inertial Measurement Systems LI.COM.
Rocket Flight Dynamics Section 1, Team 4 Student 1, Student 2, Student 3 May 5, 2008.
Final Design Presentation AUVSI 2013 Student Unmanned Air Systems Competition Team 6: Autonomous Ariel Vehicle Robert Woodruff Matthew Yasensky Cristopher.
Hendrik Hellmers, Abdelmoumen Norrdine ,
ES 100 Micro Air Vehicle Project Montgomery College Professor: Dr. Charles Kung Summer I 2012 Team Members: Andrew Joe Laura Mohammed Nathelie Noella Stephanie.
Design Team # 4 Design of low cost flight computer for unmanned aerial vehicles Status Report # 5 Ryan Morlino Chris Landeros Sylvester Meighan Stephen.
Electronics and Control System Design and Development Seth Bourn with Ted Hench, Kevin McIntire, & Sonya Pursehouse.
Interim Design Review AUVSI 2013 Student Unmanned Air Systems Competition Team 6: Autonomous Ariel Vehicle Robert Woodruff Matthew Yasensky Cristopher.
A Low-Cost and Fail-Safe Inertial Navigation System for Airplanes Robotics 전자공학과 깡돌가
Mid Semester 2 Presentation: February 27, Joshua Lasseigne: Team Lead and Autopilot Programming Christopher Edwards: AGL Subsystem and Website Maintenance.
Contents: 1. Introduction 2. Gyroscope specifications 3. Drift rate compensation 4. Orientation error correction 5. Results 6. Gyroscope and odometers.
Mini Autonomous Flying Vehicle CASDE is part of the National effort to develop a Micro Air Vehicle. CASDE has chosen a Mini Vehicle, in the short term,
By: Stuti Vyas( ) Drashti Sheth( ) Jay Vala( ) Internal Guide Mr. J. N. Patel.
Wanderbot Final Presentation Autonomous Delivery Platform Kristian Gonzalez Mechanical Engineering Undergraduate IMDL Spring 2015 Kristian Gonzalez - IMDL.
EE 495 Modern Navigation Systems Kalman Filtering – Part II Mon, April 4 EE 495 Modern Navigation Systems Slide 1 of 23.
EE 495 Modern Navigation Systems
Sensor Error Characteristics By: Hector Rotstein.
2014 Sensors in Motion   Software Engineer Lead  October 10, 2014 #GHC
EE 495 Modern Navigation Systems INS Error Mechanization Mon, March 21 EE 495 Modern Navigation Systems Slide 1 of 10.
FlySpy Patent Liabilities Analysis
High Sensitivity GPS Tracking Performance in Indoor Environment with Moderate Pedestrian Traffic Conditions Nadezda Sokolova Börje Forssell
Cloud Cap Technologies
Brandon Kipphut and Ted Zhai
Evaluation and prototypical implementation of a ground-level altitude hold for multicopter Timo Rokitte.
Dr. Marcos Esterman Faculty Guide W. Casolara Project Leader
Graduate School of Electrical Engineering
High Accuracy Advanced Tactical Navigation System – ATACNAV-HA & ATACNAV-HA-SE The High Accuracy ATACNAV system (ATACNAV-HA) is the navigation grade version.
PAX River Competition UK Aerial Robotics Team University of Kentucky.
GPS + Inertial Sensor Fusion
GPS + Inertial Sensor Fusion (GISF) Fall 2013 Presentation
Dead Reckoning, a location tracking app for Android™ smartphones Nisarg Patel Mentored by Adam Schofield and Michael Caporellie Introduction Results (cont.)
Sygic Android Support Service Call
Carson Labrado and Jacob Travis
Inertial Measurement Unit (IMU) Basics
Today’s Smart Sensors January 25, 2013 Randy Frank.
Inertial Measurement Units
Modular Motion Tracking Device
Small, Lightweight Speed and Distance Sensor
Small, Lightweight Speed and Distance Sensor
PURE Learning Plan Student: Kiarash Akhlaghi Feizasar
Rudra Timsina Micah Lucas Marc Salas Advisor: Richard Messner
DRUM ANYWHERE ECE 492 Group 4 Jake Davidson - Justin Ferris - Kelvin Liang - Shivansh Singla.
Modular Motion Tracking Device
Distributed & Scalable IMU
UAV Navigation Using Signals of Opportunity
Presentation transcript:

Team AWESOME-AOC Autonomous Winged Educational Surveillance Operational Mission Experiment Using inertial navigation systems (INS) to navigate small unmanned aerial system (sUAS) when GPS is lost or inaccurate Michael du Breuil, Alex Goodan Team AWESOME-AOC

Problem Our Research What’s Next Overview Problem Our Research What’s Next Team AWESOME-AOC

Problem GPS is susceptible to exterior interference Current sUAS navigation solutions are GPS reliant Current off the shelf INS solutions degrade quickly Team AWESOME-AOC

Our Research Evaluate off the shelf sensors Projected accuracy rates Error analysis Foundation for improved INS in sUAS Team AWESOME-AOC

INS Components Accelerometer Gyroscope Magnetometer Barometer Team AWESOME-AOC

Test Platform Custom made airframe ArduPilot/PX4/PixHawk autopilot BeagleBone Black Team AWESOME-AOC

MPU-6000 Used on ArduPilot/PX4/PixHawk Cost: $15 4x4x0.9mm <1 gram Team AWESOME-AOC

VectorNav VN-200 Low-medium performance MEMS Cost: $2,000 36 x 34 x 9.5mm 14 grams (0.03 lbs) Team AWESOME-AOC

Sensonor STIM 300 High end performance MEMS Cost: $10,000 44.8 x 38.6 x 21.5mm 55 grams (0.12 lbs) Team AWESOME-AOC

KVH 1750 High performance for size Cost: $25,000 88.9 x 73.7 mm 600 grams (1.4 lbs) Team AWESOME-AOC

Scale Factor/ Misalignment IMU Error Sources System Error Noise Bias Scale Factor/ Misalignment Bias Stability Bias Instability Fixed Bias Team AWESOME-AOC

Sample Simulation (VN-200) Team AWESOME-AOC

Simulated Results Team AWESOME-AOC

Data Acquisition Time stamps – Needs to be closer to the hardware Development kit problems Repeatability Team AWESOME-AOC

What’s Next Further simulation of sensor performance Improve acquisition Flight test all available sensors Development of INS system Team AWESOME-AOC

Questions? Team AWESOME-AOC

MPU-6000 Team AWESOME-AOC

VectorNav VN-200 Team AWESOME-AOC

Sensonor STIM 300 Team AWESOME-AOC

KVH 1750 Team AWESOME-AOC

Scale Factor/ Misalignment IMU Error Sources System Error Noise Bias Scale Factor/ Misalignment Bias Stability Bias Instability Fixed Bias Team AWESOME-AOC

Questions? Team AWESOME-AOC