Autonomous Robotic Projects at Cyber Physical Systems Group Ol - - PowerPoint PPT Presentation

▶
autonomous robotic projects at cyber physical systems
SMART_READER_LITE
LIVE PREVIEW

Autonomous Robotic Projects at Cyber Physical Systems Group Ol - - PowerPoint PPT Presentation

Dec 29, 2023 443 likes •680 views

Autonomous Robotic Projects at Cyber Physical Systems Group Ol Olive iver Hftberger, Vi Vienn nna U Uni nive versit ity of Techno nology ( (Au Austria) 04/12/2013 Outline Autonomous Systems Robotic Equipment Projects and

slide-1
SLIDE 1

Autonomous Robotic Projects at Cyber Physical Systems Group

Ol Olive iver Höftberger, Vi Vienn nna U Uni nive versit ity of Techno nology ( (Au Austria)

04/12/2013

slide-2
SLIDE 2

Outline

  • Autonomous Systems
  • Robotic Equipment
  • Projects and Problems to solve
  • Outlook

2

slide-3
SLIDE 3

Autonomous Systems

  • Autonomous systems perform actions towards a goal

with a high degree of autonomy, i.e. without human interaction.

3

  • System needs ability to
  • Gain information about

environment

  • Plan actions to reach the goal
  • Move and Interact with the

environment

  • Collaborate with other systems
slide-4
SLIDE 4

Robotic Equipment - Robots

  • 3 x MobileRobots Pioneer 3-AT
  • External Features:
  • SICK LMS 100 Laser Scanner
  • 0.5 – 20 m operating range
  • 270° field of view
  • Cannon VC-C50i PTZ Analog Camera
  • UHF RFID-Reader
  • Cyton Gamma 300 Manipulator Arm
  • 300 g payload
  • 53.4 cm total reach
  • Sonar Distance Sensors
  • Bumper Switches

4

slide-5
SLIDE 5

Robotic Equipment – Embedded Computers

  • Mamba Dual-Core, 2.26 GHz, 2 GB RAM,

60 GB SSD-Drive

  • CARMA GPU Development Kit
  • NVIDIA Tegra 3 ARM Cortex A9 Quad-Core,

2 GB RAM

  • NVIDIA Quadro 1000M with 96 CUDA Cores,

2 GB RAM

  • 120 GB SSD-Drive
  • WiFi and Ethernet Interfaces
  • Ubuntu Linux Operating System

5

slide-6
SLIDE 6

Robotic Equipment – Sensors

  • Proprietary Sensor Platform
  • Raspberry Pi, Model B, 700 MHz,

512 MB RAM

  • Sensors:
  • 3 x 3D Acceleration Sensors
  • 3D Gyroscopes
  • Digital Compass
  • Temperature Sensor
  • Pressure Sensor

6

slide-7
SLIDE 7

Robotic Equipment - Quadcopters

  • 2 x AscTec Pelican Drohnes
  • Linux Operating System

1)

1.6 GHz Intel Atom Processor Board, Laser Scanner 0.06 – 4 m range

2)

2.1 GHz Intel Core i7 Quad-Core Board, CMOS Camera

  • 3 x Parrot AR.Drone2.0
  • Front (720p) and Floor (QVGA) Camera
  • Sonar Distance Sensors
  • Controllable via Smart Phone App

7

slide-8
SLIDE 8

Robot Operating System (ROS) 1/2

  • Software framework for robots providing OS-like

functionality on heterogeneous computer cluster

  • Developed 2007 by Stanford Artificial

Intelligence Laboratory

  • Now further developed by Willow Garage
  • Seamless distribution of nodes
  • Linux, Windows, Mac OS X support
  • Implemented in C++ and Python, but other

languages supported

  • Many ROS packages available (e.g., perception,

planning, control, etc.)

8

slide-9
SLIDE 9

Robot Operating System (ROS) 2/2

  • Service Oriented Architecture
  • Publish-subscribe communication pattern
  • Node creation and destruction during runtime
  • Module-based development

9

slide-10
SLIDE 10

Mapping, Localization and Planning

  • Mapping: creation of map of

unknown environment

  • Localization: determination of

location within given map

  • Simultaneous Localization and

Mapping (SLAM)

  • Planning: organizing sequence of

actions to reach a goal

10

slide-11
SLIDE 11

Probabilistic Information in Maps

  • Types of maps:
  • Static maps (e.g., street map)
  • Dynamic maps (e.g., weather map)
  • Probabilistic maps
  • Regions marked as possible
  • bstacle (e.g., doors, objects,

persons, …)

  • Improved localization and

action planning

11

slide-12
SLIDE 12

Mapping Dynamic Areas 1/2

12

slide-13
SLIDE 13

Mapping Dynamic Areas 2/2

13

slide-14
SLIDE 14

Localization with Particle Filter

14

  • Particle: possible location of robot
slide-15
SLIDE 15

Localization with Particle Filter

15

slide-16
SLIDE 16

Vision-based Sensors

  • Determine
  • Motion of vehicle
  • Rotation of vehicle
  • Optical Flow or

FFT-based method

  • Adaptation to quality
  • f underground and

driving situation

  • GPU Implementation

16

slide-17
SLIDE 17

Sensor Fusion

“The integration of information from multiple sources to produce specific and comprehensive unified data about an entity.“ [Hal97]

17

  • Increase accuracy of sensor measurement
  • Generic Sensor Fusion and Filtering Framework

Implemented as ROS Packages

  • Voting
  • Averaging
  • Kalman Filters
  • …
slide-18
SLIDE 18

Dynamic Reconfiguration

18

  • System Ontology
  • Machine-readable model of a

system

  • Interdependence between system

properties

  • Substitution of Failed Services
  • Increase of system dependability
  • Automatic exploitation of

redundancy

  • Automatic Sensor Fusion and

Filtering

slide-19
SLIDE 19

Communication between Autonomous Systems

  • Car2Car, Car2Infrastructure, ...
  • E.g., used to optimize road traffic
  • Automatic data exchange upon system encounter
  • Avoidance of data overflow
  • Validity of data
  • Temporal validity
  • Data dependent conditions

19

Quelle: http://antyweb.pl/samochody-beda-rozmawiac-miedzy-soba-nadchodzaca- nowosc-od-mercedesa/

slide-20
SLIDE 20

Communication Framework

20

slide-21
SLIDE 21

Autonomous Collaboration (Outlook)

21

  • Collaborative actions to reach a common goal
  • Interaction of robots with different capabilities (e.g.,

rovers, drones)

  • Example scenarios:

1.

One rover uses camera to detect an object; a second rover uses the robot arm to pick the object

2.

Drone inspects the terrain of the environment to guide a rover through

slide-22
SLIDE 22

Questions?

22

... thank you!

Oliver Höftberger – oliver.hoeftberger@tuwien.ac.at