EE 495 Modern Navigation Systems

Slides:



Advertisements
Similar presentations
1 A Portable and Cost-effective Configuration of Strap-down INS/GPS for General-purpose Use * Masaru Naruoka (Univ. of Tokyo) Takeshi Tsuchiya (Univ. of.
Advertisements

1 C02,C03 – ,27,29 Advanced Robotics for Autonomous Manipulation Department of Mechanical EngineeringME 696 – Advanced Topics in Mechanical Engineering.
Mechatronics 1 Weeks 5,6, & 7. Learning Outcomes By the end of week 5-7 session, students will understand the dynamics of industrial robots.
Looking for a dynamic model of a bicycle and rider system: - Simple - Clear - Compliant with Simulink.
SPECIAL RELATIVITY Background (Problems with Classical Physics) Classical mechanics are valid at low speeds But are invalid at speeds close to the speed.
Manipulator Dynamics Amirkabir University of Technology Computer Engineering & Information Technology Department.
PHYS 218 sec Review Chap. 4 Newton’s laws of motion.
ATMOSPHERIC REENTRY TRAJECTORY MODELING AND SIMULATION: APPLICATION TO REUSABLE LAUNCH VEHICLE MISSION (Progress Seminar Presentation - 2) K. Sivan (Roll.
Ryan Roberts Gyroscopes.
Chris Hall Aerospace and Ocean Engineering
Dynamics of Serial Manipulators
Game Physics – Part II Dan Fleck. Linear Dynamics Recap  Change in position (displacement) over time is velocity  Change in velocity over time is acceleration.
Robot Dynamics – Newton- Euler Recursive Approach ME 4135 Robotics & Controls R. Lindeke, Ph. D.
The L-E (Torque) Dynamical Model: Inertial Forces Coriolis & Centrifugal Forces Gravitational Forces Frictional Forces.
ME Robotics Dynamics of Robot Manipulators Purpose: This chapter introduces the dynamics of mechanisms. A robot can be treated as a set of linked.
Manipulator Dynamics Amirkabir University of Technology Computer Engineering & Information Technology Department.
Course AE4-T40 Lecture 2: 2D Models Of Kite and Cable.
An INS/GPS Navigation System with MEMS Inertial Sensors for Small Unmanned Aerial Vehicles Masaru Naruoka The University of Tokyo 1.Introduction.
Game Physics – Part IV Moving to 3D
Computer Vision Group Prof. Daniel Cremers Autonomous Navigation for Flying Robots Lecture 3.2: Sensors Jürgen Sturm Technische Universität München.
Physics 311 Classical Mechanics Welcome! Syllabus. Discussion of Classical Mechanics. Topics to be Covered. The Role of Classical Mechanics in Physics.
Sérgio Ronaldo Barros dos Santos (ITA-Brazil)
1 C03 – Advanced Robotics for Autonomous Manipulation Department of Mechanical EngineeringME 696 – Advanced Topics in Mechanical Engineering.
The L-E (Torque) Dynamical Model: Inertial Forces Coriolis & Centrifugal Forces Gravitational Forces Frictional Forces.
Mechanics 105 Kinematics – answers the question “how?” Statics and dynamics answer the question “why?” Force Newton’s 1 st law (object at rest/motion stays.
INTRODUCTION TO DYNAMICS ANALYSIS OF ROBOTS (Part 3)
Dynamics and Control of Space Vehicles
Karman filter and attitude estimation Lin Zhong ELEC424, Fall 2010.
Inertial Navigation System Overview – Mechanization Equation
ADCS Review – Attitude Determination Prof. Der-Ming Ma, Ph.D. Dept. of Aerospace Engineering Tamkang University.
Summary for Chapters 2  4 Kinematics: Average velocity (Instantaneous) velocity  Average acceleration = (Instantaneous) acceleration = Constant acceleration:
EE 495 Modern Navigation Systems Navigation Mathematics Friday, January 9 EE 495 Modern Navigation Systems Slide 1 of 14.
EE 495 Modern Navigation Systems Inertial Sensors Monday, Feb 09 EE 495 Modern Navigation Systems Slide 1 of 19.
Robotics II Copyright Martin P. Aalund, Ph.D.
EE 495 Modern Navigation Systems Wednesday, January 13 EE 495 Modern Navigation Systems Slide 1 of 18.
INTRODUCTION TO DYNAMICS ANALYSIS OF ROBOTS (Part 4)
EE 460 Advanced Control and System Integration
Objective: To develop a fully-autonomous control system for the Q-ball based on onboard IMU/Magnetometer/Ultrasound sensory information Summer Internship.
Lecture 3: Dynamic Models
EE 495 Modern Navigation Systems
EE 495 Modern Navigation Systems Inertial Navigation in the ECEF Frame Friday, Feb 20 EE 495 Modern Navigation Systems Slide 1 of 10.
EE 495 Modern Navigation Systems Wednesday, January 8 EE 495 Modern Navigation Systems Slide 1 of 18.
EE 495 Modern Navigation Systems Navigation Mathematics Angular Velocity Monday, Jan 26 EE 495 Modern Navigation Systems Slide 1 of 8.
EE 495 Modern Navigation Systems Aided INS Monday, April 07 EE 495 Modern Navigation Systems Slide 1 of 10.
EE 495 Modern Navigation Systems Navigation Mathematics Earth Surface and Gravity Wednesday, Feb EE 495 Modern Navigation Systems Slide 1 of 14.
EE 495 Modern Navigation Systems Inertial Sensors Wed, Feb 17 EE 495 Modern Navigation Systems Slide 1 of 18.
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
9/2/2015PHY 711 Fall Lecture 41 PHY 711 Classical Mechanics and Mathematical Methods 10-10:50 AM MWF Olin 103 Plan for Lecture 4: Chapter 2 – Physics.
EE 495 Modern Navigation Systems INS Error Mechanization Mon, March 21 EE 495 Modern Navigation Systems Slide 1 of 10.
EE 495 Modern Navigation Systems TAN Error Mechanization Fri, March 25 EE 495 Modern Navigation Systems Slide 1 of 7.
Robot Dynamics – Newton- Euler Recursive Approach
EE 440 Modern Navigation Systems
EE 495 Modern Navigation Systems
Introduction To Robotics
Lecture Rigid Body Dynamics.
Lecture 16 Newton Mechanics Inertial properties,Generalized Coordinates Ruzena Bajcsy EE
This is a trivial result:
PHY 711 Classical Mechanics and Mathematical Methods
ME321 Kinematics and Dynamics of Machines
Uniform Circular Motion
Inertial Measurement Unit (IMU) Basics
TEST OF GOCE EGG DATA FOR SPACECRAFT POSITIONING
Closing the Gaps in Inertial Motion Tracking
Manipulator Dynamics 2 Instructor: Jacob Rosen
ME321 Kinematics and Dynamics of Machines
PHY 711 Classical Mechanics and Mathematical Methods
RocketSat VII Construction of an Attitude Determination System for a Sounding Rocket COSGC Symposium April 9, 2011.
PHY 711 Classical Mechanics and Mathematical Methods
( ) Lagrangian Control Volume < > < l < l = ( , , ) l l l
Presentation transcript:

EE 495 Modern Navigation Systems Inertial Navigation in the ECI Frame Wed, Feb 18 EE 495 Modern Navigation Systems

EE 495 Modern Navigation Systems Inertial Navigation in the ECI Frame Background– The Fundamental Problem The Fundamental Inertial Navigation Problem: Using inertial sensors (accels & gyros) and an initial position and orientation, determine the vehicle’s (i.e., body frame) current position, velocity, and attitude (PVA) Assumptions: Know where we started (initial PVA: 𝑟 ?𝑏 ? , 𝑣 ?𝑏 ? , & 𝐶 𝑏 ? ) Inertial sensors ( 𝜔 𝑖𝑏 𝑏 and 𝑓 𝑖𝑏 𝑏 ) are error free (relax later) Have a gravity ( 𝑔 𝑏 ? ) and/or gravitational ( 𝛾 ?𝑏 ? ) model QUESTION: Where am I ? – Current PVA ? With respect to which frame? Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Background – Inertial Navigation The process of “integrating” angular velocity & acceleration to determine one’s position, velocity, and attitude (PVA) Effectively “dead reckoning” To measure the acceleration and angular velocity vectors we need at least 3-gyros and 3-accels Typically configured in an orthogonal triad The “mechanization” can be performed wrt: The ECI frame, The ECEF frame, or The Nav frame. Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Background – ISA, IMU, & INS An Inertial Navigation System (INS) ISA – Inertial Sensor Assembly Typically, 3-gyros + 3-accels + basic electronics (power, ADCs, …) IMU – Inertial Measurement Unit ISA + Compensation algorithms (i.e., basic processing) INS – Inertial Navigation System IMU + gravity model + “mechanization” algorithms INS Mechanization Equations Initialization Gravity Model Position Velocity Attitude IMU Compensation Algorithms ISA Accels Gyros Raw sensor signals Wed, Feb 18 EE 495 Modern Navigation Systems

Mechanization Equations Inertial Navigation in the ECI Frame Background – The Mechanization Process Current IMU Measurements gyro accel Mechanization Equations Prior Attitude Prior Velocity Prior Position Gravity / Gravitational Model Prior PVA Updated Attitude Updated Velocity Updated Position Updated PVA Wed, Feb 18 EE 495 Modern Navigation Systems

EE 495 Modern Navigation Systems Inertial Navigation in the ECI Frame Background – A Four Step Mechanization Process Can be generically performed in four steps: Attitude Update Update the prior attitude (rotation matrix) using the current angular velocity measurement ( 𝐶 1 0 = 𝐶 1 0   𝛺 01 1 = 𝛺 01 0 𝐶 1 0  ) Transform the specific force measurement ( 𝑓 𝑖𝑏 ? = 𝐶 𝑏 ? 𝑓 𝑖𝑏 𝑏 ) Typically, using the attitude computed in step 1. Update the velocity Essentially, integrate the result from step 2. with the use of a gravity/gravitation model ( 𝑓 𝑖𝑏 = 𝑎 𝑖𝑏 − 𝛾 𝑖𝑏 ) Update the Position Essentially, integrate the result from step 3. Wed, Feb 18 EE 495 Modern Navigation Systems

EE 495 Modern Navigation Systems Inertial Navigation in the ECI Frame Background – A Four Step Mechanization IMU Measurements Prior Attitude 1. Attitude Update 2. SF Transform Prior Velocity 3. Velocity Update Grav Model Prior PVA Prior Position 4. Position Update Updated Attitude Updated Velocity Updated Position Updated PVA Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Case 1: ECI Mechanization CASE 1: ECI Frame Mechanization Determine the Position, Velocity, and Attitude of the Body frame with respect to the Inertial Frame Determine our PVA wrt the ECI frame Position: Vector from the origin of the inertial frame to the origin of the body frame resolved in the inertial frame: 𝑟 𝑖𝑏 𝑖 Velocity: Velocity of the body frame wrt the inertial frame resolved in the inertial frame: 𝑣 𝑖𝑏 𝑖 Attitude: Orientation of the body frame wrt the inertial frame 𝐶 𝑏 𝑖 Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Case 1: ECI Mechanization 1. Attitude Update: Method A Body orientation frame at time “k” wrt time “k-1” t = Timek – Timek-1 Body Frame at time “k” Body Frame at time “k-1” Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Case 1: ECI Mechanization 1. Attitude Update: Method B Body orientation frame at time “k” wrt time “k-1” t = Timek – Timek-1 Body Frame at time “k” Body Frame at time “k-1” Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Case 1: ECI Mechanization 1. Attitude Update: High Fidelity Lower Fidelity Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Case 1: ECI Mechanization 2. Specific Force Transformation Simply coordinatize the specific force 3. Velocity Update Assuming that we are in space (i.e., no centrifugal component) Thus, by simple numerical integration 4. Position Update By simple numerical integration Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Case 1: ECI Mechanization 1. Attitude Update 2. SF Transform or Grav Model 3. Velocity Update 4. Position Update Wed, Feb 18 EE 495 Modern Navigation Systems

Inertial Navigation in the ECI Frame Case 1: ECI Mechanization In continuous time notation: Attitude: 𝐶 𝑏 𝑖 = 𝐶 𝑏 𝑖   𝛺 𝑖𝑏 𝑏 Velocity: 𝑣 𝑖𝑏 𝑖 = 𝐶 𝑏 𝑖   𝑓 𝑖𝑏 𝑏 + 𝛾 𝑖𝑏 𝑖 Position: 𝑟 𝑖𝑏 𝑖 = 𝑣 𝑖𝑏 𝑖 Combining into a state-space equation: Wed, Feb 18 EE 495 Modern Navigation Systems