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Autonomous Robotic Projects at Cyber
Physical Systems Group
Oliver Höftberger, Vienna University of Technology (Austria)
04/12/2013
Outline
• Autonomous Systems
• Robotic Equipment
• Projects and Problems to solve
• Outlook
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Autonomous Systems
• Autonomous systems perform actions towards a goal with a high degree of autonomy, i.e. without human interaction.
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• System needs ability to • Gain information about
environment
• Plan actions to reach the goal
• Move and Interact with the environment
• Collaborate with other systems
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
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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
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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
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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
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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.)
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Robot Operating System (ROS) 2/2
• Service Oriented Architecture • Publish-subscribe communication pattern
• Node creation and destruction during runtime
• Module-based development
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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
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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 obstacle (e.g., doors, objects, persons, …)
• Improved localization and action planning
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Mapping Dynamic Areas 1/2
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Mapping Dynamic Areas 2/2
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Localization with Particle Filter
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• Particle: possible location of robot
Localization with Particle Filter
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Vision-based Sensors
• Determine • Motion of vehicle
• Rotation of vehicle
• Optical Flow or FFT-based method
• Adaptation to quality of underground and driving situation
• GPU Implementation
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Sensor Fusion
“The integration of information from multiple sources to produce specific and comprehensive unified data about an entity.“ [Hal97]
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• Increase accuracy of sensor measurement
• Generic Sensor Fusion and Filtering Framework Implemented as ROS Packages
• Voting
• Averaging
• Kalman Filters
• …
Dynamic Reconfiguration
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• 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
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
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Quelle: http://antyweb.pl/samochody-beda-rozmawiac-miedzy-soba-nadchodzaca-nowosc-od-mercedesa/
Communication Framework
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Autonomous Collaboration (Outlook)
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• 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
