Fiches de cours 2017-2018

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Localization and Navigation Methods

ENV-719

Lecturer(s) :

Botteron Cyril
Martinoli Alcherio
Merminod Bertrand
Skaloud Jan

Language:

English

Frequency

Every 2 years

Remarque

Next time: Fall 2018

Summary

Transmitting to the student state-of-the art methods and research topics in localization and navigation algorithms and systems. Students will be able to put in practice their knowledge in a course project and by three labs involved in the course. Lectures are concentrated in the first 5 weeks.

Content

Week 1: Satellite positioning (Prof. Bertrand Merminod)

'           Satellite orbit motion, Kepler's laws, broadcast and precise ephemeris

'           Description of GPS signal structure and derivation of observables

'           Inventory of error sources, random and non-random effects

'           Derivation of mathematical models for absolute and differential positioning.

'           Estimation of the position and its precision based on least-square principle analysis

'           Overview of GNSS

'           Lab assignments: Absolute GPS positioning with and without approximation

Week 2: Wireless location and state-space estimation (Dr. Cyril Botteron)

'           Fundamentals of radio-frequency propagation and positioning

'           Time and angle observables and associated error sources

'           Kalman filtering applied to kinematic positioning

'           Location with wireless computer network

'           Ultra-wide band positioning principles

'           Outdoor and indoor personal location, asset tracking

'           Lab assignment: Kalman Filtering in kinematic positioning

Week 3: Trajectory and attitude determination with INS/GNSS (Dr. Jan Skaloud)

'           Inertial sensors, inertial systems 

'           Linear dynamical systems, stochastic differential equations

'           Inertial strapdown mechanization equations in (i,e,n) frames

'           INS strapdown error equations and calibration states

'           Alignment models

'           Redundant IMU configurations

'           Prediction, filtering, smoothing and calibration

'           No lab assignments

Week 4: Trajectory and attitude determination via optical positioning and dynamic networks, integrated sensor orientation (Dr. Jan Skaloud)

'           Colineraity condition for 0-D, 1-D and 2-D optical sensors

'           Sensor models and observations, feature matching

'           Principle of integrated sensor orientation. Orientation vs calibration

'           Formulation of INS/GNSS/optical-sensor case in dynamic networks, numerical issues

'           Lab assignment to select among visionary sensors; 1. oscillating cams & ALS; 2.
            1-line-camera and ALS; etc. 

Week 5: Localization and Navigation in Mobile Robotics (Prof. Alcherio Martinoli)

'           Overview of localization techniques in mobile robotics  (off-board/on-board;
             absolute/relative)

'           Basic kinematic models (differential drive, Ackerman steering vehicles)

'           Odometry

'           Feature-based localization

'           Kalman filtering and particle filtering techniques applied to mobile robots

'           Multi-robot localization

'           Fundamental of navigation (path planning, landmark-based navigation)

'           No lab assignments

Keywords

Navigation, Localization, Kalman Filtering, Estimation Methods

Learning Prerequisites

Required courses

Least-square adjustment.

 

 

Recommended courses

Recommended Bachelor courses:
Advanced Satellite Positioning and/or Sensor Orientation.

Learning Outcomes

By the end of the course, the student must be able to:

Resources

Websites
Moodle Link

In the programs

Reference week

 
      Lecture
      Exercise, TP
      Project, other

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  • Autumn semester
  • Winter sessions
  • Spring semester
  • Summer sessions
  • Lecture in French
  • Lecture in English
  • Lecture in German