Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm
Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm
Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm
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<strong>Session</strong> WedDT4 Fenix 3 <strong>Wednesday</strong>, <strong>October</strong> <strong>10</strong>, <strong>2012</strong>, 14:00–15:00<br />
Humanoid Robots V<br />
Chair<br />
Co-Chair<br />
14:00–14:15 WedDT4.1<br />
Humanoid Push Recovery<br />
with Robust Convex Synthesis<br />
Jiuguang Wang<br />
Robotics Institute, Carnegie Mellon University<br />
robot@cmu.edu<br />
• Humanoid full-body push recovery<br />
• Robust control design – model bounded<br />
external disturbances<br />
• Simultaneously search for a controller and<br />
the associated domain of attraction using<br />
convex optimization<br />
• The controller guarantees stabilization<br />
under bounded disturbances as well as<br />
physical constraints on the robot<br />
14:30–14:45 WedDT4.3<br />
Lower Thigh Design of<br />
Detailed Musculoskeletal Humanoid “Kenshiro”<br />
Yuki Asano*, Hironori Mizoguchi**, Toyotaka Kozuki**,<br />
Yotaro Motegi**, Masahiko Osada**, Junichi Urata**,<br />
Yuto Nakanishi**, Kei Okada** and Masayuki Inaba**<br />
*Graduate School of Interdisciplinary Information Studies, Univ.of Tokyo, Japan<br />
**Dept. of Mechano-Informatics, Univ.of Tokyo, Japan<br />
• Design concept of Detailed<br />
Musculoskeletal Humanoid “Kenshiro”<br />
• Body Configuration<br />
• Joint Structure<br />
• Muscle Arrangement<br />
• Biomimetic Design of the Knee Joint<br />
• Kneecap<br />
• Cruciate Ligament<br />
• Screw-Home Mechanism<br />
• Detailed Muscle Arrangement Imitating<br />
Human<br />
• Experiment of Knee Rotation on the<br />
Ground<br />
Detailed musculoskeletal humanoid<br />
“Kenshiro”. Knee rotation experiment<br />
and muscle arrangemant of leg<br />
14:15–14:30 WedDT4.2<br />
Appearance-Based Traversability<br />
Classification in Monocular Images Using<br />
Iterative Ground Plane Estimation<br />
Daniel Maier and Maren Bennewitz<br />
Department of Computer Science, University of Freiburg, Germany<br />
• Traversability estimation from monocular<br />
camera images for robot navigation<br />
• Learning appearance-based classifiers for<br />
fast and dense classification of images<br />
• Classifiers are updated online in a selfsupervised<br />
fashion<br />
• Iterative detection and matching of sparse<br />
features on the ground plane under the<br />
homography constraint<br />
• Classified images are integrated into an<br />
occupancy grid map<br />
• Experiments with a real humanoid robot<br />
show high classification rates and robust<br />
obstacle detection<br />
<strong>2012</strong> IEEE/RSJ International Conference on Intelligent Robots and Systems<br />
–154–<br />
Top: Sparse Floor Features<br />
Bottom: Dense Classification<br />
14:45–15:00 WedDT4.4<br />
Optimization-based generation and experimental<br />
validation of walking trajectories for biped robots<br />
Alexander Werner, Roberto Lampariello and Christian Ott<br />
Institute of Robotics and Mechatronics, Deutsches Zentrum für Luft- und<br />
Raumfahrt (DLR), Germany<br />
• Generation of energy-optimal step<br />
trajectories through non-linear<br />
programming with full rigid-body robot<br />
model<br />
• Stability(ZMP), collisions and joint limits<br />
are respected<br />
• Efficient fixed-based calculation of the<br />
constraints and the cost function<br />
• Analysis and avoidance of global minima<br />
• Experimental testing and evaluation of the<br />
trajectories<br />
• Significant gain (55%) in the cost function<br />
with respect to capture-point based<br />
controller<br />
Optimal Walking Trajectories