The European Project sFly: Swarm of Micro Flying Robots www.sfly.org EU FP7, 2009-2011 www.sfly.org.

Slides:



Advertisements
Similar presentations
Robotics at ENSTA Bretagne Fabrice LE BARS. Robotics at ENSTA Bretagne 17/05/ Robotics at ENSTA Bretagne Main research areas : Autonomous marine.
Advertisements

Georgia Tech Aerial Robotics Dr. Daniel P Schrage Jeong Hur Fidencio Tapia Suresh K Kannan SUCCEED Poster Session 6 March 1997.
Nonlinear Control of Quadrotor
Waterloo Aerial Robotics Group WARG Mandate: The Waterloo Aerial Robotics Group is a team of University of Waterloo students who, with the support of our.
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.
HAWK Helicopter Aircraft Wielding Kinect Kevin Conley (EE ’12), Paul Gurniak (EE ’12), Matthew Hale (EE ’12), Theodore Zhang (EE ’12) – Team 6, 2012 Advisor:
Design Presentation Spring 2009 Andrew Erdman Chris Sande Taoran Li.
Gilbert Islas Feb. 25, 2012 SYSM  A micro air vehicle (MAV) is a class of unmanned aerial vehicles (UAV). unmanned aerial vehicles  Size restrictions.
The Micro-CART project will develop a fully autonomous UAV for the 2007 International Aerial Robotics Competition. The industry-sponsored project is funded.
Luis Mejias, Srikanth Saripalli, Pascual Campoy and Gaurav Sukhatme.
Autonomous Cargo Transport System for an Unmanned Aerial Vehicle, using Visual Servoing Noah Kuntz and Paul Oh Drexel Autonomous Systems Laboratory Drexel.
Automatic Control & Systems Engineering Autonomous Systems Research Mini-UAV for Urban Environments Autonomous Control of Multi-UAV Platforms Future uninhabited.
Image Processing of Video on Unmanned Aircraft Video processing on-board Unmanned Aircraft Aims to develop image acquisition, processing and transmission.
1 AE - Control and Simulation – Micro Air Vehicle laboratory Flying Robots : the MAV-lab - Delfly: 3g, 10 cm, camera - Guinness book of records - Autonomous.
Client: Space Systems & Controls Laboratory (SSCL) Advisor : Matthew Nelson Anders Nelson (EE) Mathew Wymore (CprE)
April 26, Team Information Designation Ongo-03 Members Advisors Dr. J. Lamont, Prof. R. Patterson, Dr. Rajagopalan, Dr. J. Basart ClientSpace Systems.
Micro-CART Microprocessor-Controlled Aerial Robotics Team May 1, 2002 Team - Ongo03.
Μ - CART Microprocessor – Controlled Aerial Robotics Team (Ongo03) An Ongoing Senior Design Project Department of Electrical and Computer Engineering Iowa.
Better Robots 1 The Goal: More Robots Enabling Fewer Soldiers Military “robots” today lack autonomy –Currently, many soldiers control one robot –Want few.
A New Method for the Tele-operation of Aircraft Dr. Paul Oh James Hing.
Embedded Microcomputer Systems Andrew Karpenko 1 Prepared for Technical Presentation February 25 th, 2011.
1 DTSI / Interactive Robotics Unit IST Advanced Robotics µdrones µDRone autOnomous Navigation for Environment Sensing JM ALEXANDRE CEA List.
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.
The Trimble Technology Timeline Evolution of GPS Technology – Applications in the Unmanned World Akshay Bandiwdekar Product Portfolio Manager – Avionics.
Development of a Mini-UAV for Urban Environments Tony Dodd and Beniamin Apopei.
Real-time Dense Visual Odometry for Quadrocopters Christian Kerl
Development of Control for Multiple Autonomous Surface Vehicles (ASV) Co-Leaders: Forrest Walen, Justyn Sterritt Team Members: Andrea Dargie, Paul Willis,
ICRA 2014 TREVEL REPORT Chang-Ryeol Lee May 30 – June 5, 2014.
Joint International Master Project Dennis Böck & Dirk C. Aumueller 1.
Multiple Autonomous Ground/Air Robot Coordination Exploration of AI techniques for implementing incremental learning. Development of a robot controller.
1.  The Autonomous Helicopter Navigation System 2010 is focused on developing a helicopter system capable of autonomous control, navigation and localising.
Intelligent Mobile Robotics Czech Technical University in Prague Libor Přeučil
The Micro-CART project teaches students how to familiarize themselves with a project that they were not part of from conception to completion. Students.
Computational Mechanics and Robotics The University of New South Wales
o Portable low-cost aerial drone that can be used for reconnaissance o Relay real-time video and data, like location, heading, battery life o Take high-resolution.
Sérgio Ronaldo Barros dos Santos (ITA-Brazil)
Outline Previous Accomplishments o Last year's SURG o Mapkin Proposal Concept o Why is this useful? o The MikroKopter platform o Previous work Criteria.
AEM 5333 UAV Search and Surveillance. Mission Description Overhead surveillance and tracking – Humans on foot – Moving vehicles Onboard GPS transceiver.
Computer Vision Group Prof. Daniel Cremers Autonomous Navigation for Flying Robots Lecture 2.3: 2D Robot Example Jürgen Sturm Technische Universität München.
Computer Vision Driven Micro- Aerial Vehicle (MAV): Obstacles Avoidance Lim-Kwan (Kenny) Kong - Graduate Student Dr. Jie Sheng - Faculty Advisor Dr. Ankur.
Autonomous Air & Ground Surveillance Unit Objectives, Preliminary Specifications, and Option Analysis.
W.A.S.P. Wi-Fi Aerial Surveillance Platform. W.A.S.P. Small Scale, Open Source UAV using off the shelf components Designed to provide a vehicle to project.
10/19/2005 ACGSC Fall Meeting, Hilton Head SC Copyright Nascent Technology Corporation © 2005 James D. Paduano 1 NTC ACTIVITIES 2005 Outline 1)Activities.
Cooperative Air and Ground Surveillance Wenzhe Li.
Towards Establishing and Maintaining Autonomous Quadrotor Formations Audrow J. Nash William Lee College of Engineering University of North Carolina at.
MASKS © 2004 Invitation to 3D vision. MASKS © 2004 Invitation to 3D vision Lecture 1 Overview and Introduction.
Computer Vision Group Prof. Daniel Cremers Autonomous Navigation for Flying Robots Lecture 1.2: Why Quadrotors? Jürgen Sturm Technische Universität München.
Funding provided by: Clients Iowa Space Consortium Department of Electrical and Computer Engineering Advisors Dr John Lamont, Professor E/Cpr E Dr Ralph.
Existing Draganflyer Projects and Flight Model Simulator Demo Chayatat Ratanasawanya 5 February 2009.
MAV’08 Research Update Abe Bachrach Ruijie He Sam Prentice Nicholas Roy Feb 14, 2008 Happy Valentine’s!
NAVIGATIONAL AUTONOMY USING QUADCOPTERS By Alessandro Triaca.
1 Center for the Collaborative Control of Unmanned Vehicles (C3UV) UC Berkeley Karl Hedrick, Raja Sengupta.
Univ logo Robotics for Nuclear Decommissioning Drone-Arm Cooperative Vision Thomas Burrell C.J. Taylor, S.D. Monk, A. Montazeri Lancaster University –
Design Team # 4 Design of low cost flight computer for unmanned aerial vehicles Status Report # 5 Ryan Morlino Chris Landeros Sylvester Meighan Stephen.
Optic Flow QuadCopter Control
Abstract Each July, the Association for Unmanned Vehicle Systems International holds an annual International Aerial Robotics Competition (IARC), with major.
Chayatat Ratanasawanya May 18, Overview Recalls Progress & Achievement Results 2.
Planning in Information Space for a Quad-rotor Helicopter Ruijie He Thesis Advisor: Prof. Nicholas Roy.
WORKING PRINCIPLE – MOTOR ROTATION BACKWARD MOTION FORWARD MOTION.
By: Stuti Vyas( ) Drashti Sheth( ) Jay Vala( ) Internal Guide Mr. J. N. Patel.
QUADCOPTER.
MASKS © 2004 Invitation to 3D vision. MASKS © 2004 Invitation to 3D vision Lecture 1 Overview and Introduction.
Minor Project on Vertical Take-off Landing System SUBMITTED BY:- SHUBHAM SHARMA ( ) ABHISHEK ARORA ( ) VIBHANSHU JAIN ( )
Establishing and Maintaining Formations of Mini Quadrotors Audrow J. Nash, Cory M. Engel, James M. Conrad William Lee College of Engineering University.
Micro-CART SDongo3b Secondary Vehicle Team April 26, 2006
The JAviator Project Rainer Trummer Computer Sciences Workshop '06
Najib METNI François DERKX Jean-Luc SORIN
Mobile Vision for Autonomous…
Quanser Robotic Product Line 2015
Presentation transcript:

The European Project sFly: Swarm of Micro Flying Robots EU FP7,

Micro-UAVs for Rescue and Inspection  Autonomous micro helicopters are about to play major roles in tasks like:  search and rescue  environment monitoring  inspection  Access to environments where no human or other vehicles gets access to,  Reducing the risk for the environment and people Inspector x y z  Personnel operates in high risk environmentReplace by tele-operated aerial inspection vehicle

Consortium  Switzerland  ETH Autonomous Systems Lab (leader)  ETH Computer Vision Lab  CSEM: Centre Suisse d'Electronique et de Microtechnique  France  INRIA: French National Research Institute  Greece  Techical University of Crete  Germany  Ascending Technology

sFly: objectives  Coordinated flight in small swarms in constrained and dense environments (e.g. urban)  Inter-distance estimation  Low power communication (between helicopters and with the ground station using GSM)  Inherently safe (< 1 Kg)  Capable of autonomous navigation in GPS denied environments  Vision-based fully autonomous navigation and mapping

The System The Platform  Hummingbird quadrotor helicopter from Ascending Technologies ( )  50 cm diameter  200 g additional payload  on-board IMU (roll, pitch, yaw) The camera  190º field-of-view fisheye camera On-board Processing  Intel Atom, 1.6 GHz

Evolution of the platform 1 st version: Hummingbird 2 nd version: Pelican 3rd version: Hexacopter

The Problem: Vision-based motion estimation… R, T = ? … and 3D reconstruction … without GPS. How?

How does it work? Image 1 Image 2 R, T = ?

Outdoor Results  Stable hovering at 15 m height  Large scale reconstruction form aerial images during autonomous flight

sFly: what’s the next step?  Coordinated flight with multiple helicopters using single cameras only For more info: Contact: