Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm

Session WedCT3 Pegaso B Wednesday, October 10, 2012, 11:00–12:30
Sensors, Sensor Networks and Networked Robots
Chair
Co-Chair
11:00–11:15 WedCT3.1
Semi-Autonomous Visual Inspection of Vessels
Assisted by an Unmanned Micro Aerial Vehicle
Francisco Bonnin-Pascual, Emilio Garcia-Fidalgo
and Alberto Ortiz
Department of Mathematics and Computer Science,
University of Balearic Islands, Spain
• Semi-autonomous approach to
the vessel inspection problem
making use of an autonomous
Micro Aerial Vehicle
• The vehicle provides the
surveyors with images of the
areas of the hull to be inspected
• Supplied images can be
processed by corrosion and
crack detection algorithms
based on texture, colour and
morphology
• Experimental results are
provided, which show that the
approach fulfils the application
requirements
11:30–11:45 WedCT3.3
Prioritized Multi-Task Motion Control of
Redundant Robots under Hard Joint Constraints
Fabrizio Flacco Alessandro De Luca
DIAG, Università di Roma “La Sapienza”, Italy
Oussama Khatib
Artificial Intelligence Laboratory, Stanford University, USA
• Extension to multiple prioritized tasks of
our recent SNS (Saturation in the Null
Space) algorithm for acceleration-level
control of redundant robots
• Hard bounds on joint range, velocity, and
acceleration/torque are always satisfied
• A multi-task least scaling strategy is
integrated in the SNS, when some of the
original tasks turn out to be unfeasible
• Efficient preemptive approach: A task of
higher priority uses at best all the robot
capabilities needed; lower priority tasks
exploit the residual capabilities, without
interfering with higher priority tasks
A KUKA LWR robot cycles through
Cartesian points, with self-motion
damping as the secondary task and
while satisfying all joint constraints
12:00–12:15 WedCT3.5
Entropy-aware Cluster-based Object Tracking
for Camera Wireless Sensor Networks
Alberto De San Bernabé, Jose Ramiro Martinez-de Dios and
Anibal Ollero
Robotics, Vision and Control Group, University of Seville, Spain
• Entropy-based mechanisms for energy
efficiency and robustness to transmission
errors in object tracking systems are
presented.
• Activation/deactivation of camera-nodes
using an active sensing method based on
cost-gain analyses to reduce energy
consumption.
• Method that dynamically selects the
cluster head using entropies and
transmission error rates.
• The proposed methods have been tested
in experiments carried out in the CONET
Robot-WSN Testbed (http://conet.us.es)
Picture of one experiment in the
CONET Robot-WSN Testbed
11:15–11:30 WedCT3.2
Web Mining Driven Object Locality Knowledge
Acquisition for Efficient Robot Behavior
Kai Zhou, Michael Zillich and Markus Vincze
Automation and Control Institute (ACIN), Vienna University of Technology, Austria
Hendrik Zender
Language Technology Lab, German Research Center for Artificial Intelligence (DFKI), Germany
• Probabilistic conceptual knowledge that
represents the relations of object and its
situated environments is obtained online.
• More accurate quantification is achieved
by fusing search engine query data and
professional robotic database.
• Diverse localities including various
supporting surfaces and room categories
have been investigated to find the
dominant location of object.
• Multiple objects search task has been
performed using the discovered
probabilistic knowledge.
• Plentiful experimental results (200+
objects/furniture, 3 surfaces, 7 rooms)
validate the intuition of discovering object
locality knowledge online.
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
–141–
Example scenario and object
search task
11:45–12:00 WedCT3.4
Optical-Inertial Tracking with Active Markers and
Changing Visibility
Florian Steidle and Andreas Tobergte
and Gerd Hirzinger
Robotics and Mechatronics Center,
German Aerospace Center, Germany
• Extended Kalman Filter to fuse low latency measurements of inertial
measurement unit with 2D marker measurements
• Markers, identificated by individual activation, are subsequently locally
tracked in the image pane
• Robust with respect
to temporary marker
occlusions
• Real time
implementation and
verification with
experiments
12:15–12:30 WedCT3.6
Intelligent Sensor-Scheduling for
Multi-Kinect-Tracking
Florian Faion, Simon Friedberger, Antonio Zea,
and Uwe D. Hanebeck
Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT)
• Scenario: target tracking with a Multi-
Kinect-sensor-network
• Challenge: high bandwidth, computational
cost, interference
• Idea: measuring the target exclusively with
best available sensor
• Contribution: uncertainty minimizing
scheduling algorithm, stochastic Kinect
sensor model, Kinect IR-projector
modification