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

Session WedEVT9 Fenix 1 Wednesday, October 10, 2012, 15:00–16:00
Vision for Segmentation and Servoing
Chair Aaron Bobick, Georgia Tech.
Co-Chair Dongheui Lee, Tech. Univ. of Munich
15:00–15:15 WedEVT9.1
Guided Pushing for Object Singulation
Tucker Hermans James M. Rehg
Aaron F. Bobick
Robotics and Intelligent Machines
School of Interactive Computing
Georgia Institute of Technology, USA
• Desire to separate and segment all
objects in the scene
• Accomplish through pushing
• Object boundaries lie on image edges
• Objects split at the vertical plane
through the edge
• Push parallel to thisedge through the
predicted objectcentroid
• Quantize candidate boundary
orientations for each point cloud cluster
• Stop pushing when all non-empty
directions have been tested
15:30–15:45 WedEVT9.3
Robust Visual Servoing for Object Manipulation
with Large Time-Delays of Visual Information
Akihiro Kawamura, Kenji Tahara, Ryo Kurazume
and Tsutomu Hasegawa
• New visual servoing method for object
manipulation robust to time-delays is proposed
• That is robust to
Kyushu University, Japan
� Time-delay caused by low sampling rate
� Time-delay caused by image processing
and data transmission latency
• Virtual object frame is utilized effectively
• Usefulness is demonstrated by numerical
simulations and experiments.
Actual frame and virtual frame
15:50–15:55 WedEVT9.5
Ascending Stairway Modeling: A First Step
Toward Autonomous Multi-Floor Exploration
Jeffrey Delmerico, Jason Corso and Julian Ryde
Dept. of Computer Science and Engineering, SUNY Buffalo, USA
David Baran and Philip David
US Army Research Laboratory, USA
• Goal: autonomous multi-floor
exploration by ground robots.
• Discover stairways in environment
during mapping and assess their
traversability.
• System will permit path planning to
consider stairways among
traversable terrain.
• Robust detector and accurate
modeling procedure; sufficient to
determine step dimensions to
within 2cm.
Overview of stairway modeling system: stair
detection in depth imagery, aggregation of
extracted step edge point clouds, and
generative model fitting.
15:15–15:30 WedEVT9.2
Segmentation of Unknown Objects
in Indoor Environments
A. Richtsfeld, T. Mörwald, J. Prankl, M. Zillich, M.Vincze
Automation and Control Institute (ACIN),
Vienna University of Technology, Austria
• Learning segmentation of unknown
objects from RGB-D images in a
hierarchical data abstraction framework
• Data abstraction of RGB-D images to
parametric surface patches.
• Learning of perceptual grouping rules with
support vector machines (SVM)
• Globally optimal segmentation using
Graph-Cut on SVM predictions
15:45–15:50 WedEVT9.4
Tire Mounting on a Car Using the Real-Time
Control Architecture ARCADE
Thomas Nierhoff, Lei Lou, Vasiliki Koropouli, Martin Eggers,
Timo Fritzsch, Omiros Kourakos, Kolja Kühnlenz
Dongheui Lee, Bernd Radig, Martin Buss, Sandra Hirche
Technische Universität München, Germany
• ARCADE architecture:
- hard real-time scheduling,
- asynchronous remote
procedure call,
- hardware-in-the-loop
development
• Increasing functional modules:
- autonomous navigation,
- haptic interaction/perception,
- human-robot/multi-robot cooperation
• Challenges for control:
- stability of closed kinematic chains, transfer of human motions to robots
• Challenges for perception
- robust object detection in large rooms, whole environment perception
15:55–16:00 WedEVT9.6
Low cost MAV platform AR-drone in experimental verifications
of methods for vision based autonomous navigation
Martin Saska, Tomáš Krajník, Jan Faigl, Vojtěch Vonásek and Libor Přeučil
Department of Cybernetics, Faculty of Electrical Engineering,
Czech Technical University in Prague, Czech Republic.
• Video: a sequence of various Micro Aerial
Vehicle (MAV) applications and research
experiments with AR-Drone playing the
main role. http://imr.felk.cvut.cz/demos/videos/drone/
• The presented methods rely on visual
navigation and localization using on-board
cameras of the AR-drone employed in the
control feedback.
• The aim is to demonstrate flight performance
of this platform in real world tasks.
• Applications: 1) MAV-UGV teams for
inspection of inaccessible areas; 2) Autonomous
flight in outdoor environment with
human-MAV interaction; 3) AR-Drone as
an ad-hoc external localization unit for
multi-robot applications; 4) MAV for
verification of localization uncertainty
decrease in an autonomous inspection
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
–170–
Mobile
heliport
UGV camera
UAV
UAV
camera
Autonomous inspection of inaccessible
areas by MAV-UGV teams