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> WedCT4 Fenix 3 <strong>Wednesday</strong>, <strong>October</strong> <strong>10</strong>, <strong>2012</strong>, 11:00–12:30<br />
Humanoid Robots IV<br />
Chair Kyungshik Roh, Samsung Electronics Co., Ltd<br />
Co-Chair Christian Ott, German Aerospace Center (DLR)<br />
11:00–11:15 WedCT4.1<br />
Development of the Lower Limbs<br />
for a Humanoid Robot<br />
Joohyung Kim, Younbaek Lee, Sunggu Kwon, Keehong Seo,<br />
Hoseong Kwak, Heekuk Lee, and Kyungshik Roh<br />
Samsung Advanced Institute of Technology, South Korea<br />
• We Present an overview of developing a<br />
novel biped walking machine for a<br />
humanoid robot Roboray.<br />
• Torque sensors are integrated at each<br />
joint of 6-DOF legs.<br />
• A new tendon type joint module is used<br />
in a pitch joint drive module, which is<br />
highly back-drivable.<br />
• Control system is decentralized using<br />
small controller boards named Smart<br />
Driver.<br />
Roboray and its lower limbs<br />
without cover.<br />
11:30–11:45 WedCT4.3<br />
Optimal Gait Primitives for Dynamic<br />
Bipedal Locomotion<br />
Bokman Lim, Jusuk Lee, Joohyung Kim, Minhyung Lee,<br />
Hoseong Kwak, Sunggu Kwon, Heekuk Lee,<br />
Woong Kwon, and Kyungshik Roh<br />
Samsung Advanced Institute of Technology, Korea<br />
• A movement generation framework for<br />
dynamic bipedal locomotion is proposed.<br />
• A set of parametric gait primitives is first<br />
constructed using the dynamics-based<br />
movement optimization algorithm.<br />
• Dynamic walking to follow the arbitrary<br />
path is then generated online via<br />
sequentially composing primitive motions.<br />
• Proposed method is applied to a torque<br />
controlled robot platform, Roboray.<br />
• Results show that dynamic gaits are<br />
humanlike and efficient compared to the<br />
conventional knee bent walkers.<br />
Roboray<br />
12:00–12:15 WedCT4.5<br />
Robust Descriptors for 3D Point Clouds using<br />
Geometric and Photometric Local Feature<br />
Hyoseok Hwang, Seungyong Hyung, Sukjune Yoon and<br />
Kyungshik Roh<br />
Samsung Advanced Institute of Technology<br />
Samsung Electronics<br />
Republic of Korea<br />
• We propose robust descriptors called<br />
GPLF(Geometric and Photometric Local<br />
Feature) for object recognition and pose<br />
estimation<br />
• The proposed descriptors simultaneously<br />
use geometric and photometric features of<br />
point clouds from RGB-D camera<br />
• GPLF has robust discriminative ability<br />
regardless of characteristics such as<br />
shapes or appearances of objects.<br />
• The experimental results show the<br />
recognition accuracy of the proposed<br />
descriptors is higher than other<br />
approaches which use a single feature<br />
The proposed descriptors of<br />
3D point clouds<br />
11:15–11:30 WedCT4.2<br />
On-board Odometry Estimation<br />
for 3D Vision-based SLAM of Humanoid Robot<br />
SungHwan Ahn, Sukjune Yoon, Seungyong Hyung,<br />
Nosan Kwak and Kyung Shik Roh<br />
Samsung Advanced Institute of Technology (SAIT),<br />
Samsung Electronics, Korea<br />
• Vision-based 3D motion estimation<br />
method for dynamic walking robots<br />
accompanying large swaying motion and<br />
uncertainty in camera movement.<br />
• On-board odometry filter fuses kinematic<br />
odometry, visual odometry, and raw IMU<br />
data.<br />
• Vision-based SLAM utilizes the fused<br />
odometry, and it improves the SLAM<br />
estimates by compensating motion errors.<br />
• Experiments verifies the method with the<br />
biped humanoid robot, Roboray, designed<br />
by Samsung.<br />
11:45–12:00 WedCT4.4<br />
Towards Natural Bipedal Walking: Virtual Gravity<br />
Compensation and Capture Point Control<br />
Keehong Seo, Joohyung Kim, Kyungshik Roh<br />
Samsung Advanced Institute of Technology, South Korea<br />
• A pose controller is proposed that<br />
compensates Cartesian pose errors for a<br />
bipedal robot.<br />
• Virtual gravity compensation (VGC) is<br />
developed to convert 6-dof Cartesian force<br />
to joint torques in the legs.<br />
• A walking algorithm using VGC and<br />
capture point control produces natural<br />
and robust walking gait.<br />
• Tested with Roboray, humanoid from<br />
Samsung Electronics, to balance on<br />
slopes, to walk over bumps, and to<br />
recover from pushes while walking.<br />
• Resulting gait shows clear heel-landing<br />
and toe-off motions as humans do.<br />
<strong>2012</strong> IEEE/RSJ International Conference on Intelligent Robots and Systems<br />
–142–<br />
Figure caption is optional,<br />
use Arial Narrow 20pt<br />
12:15–12:30 WedCT4.6<br />
Active Stabilization of a Humanoid Robot for<br />
Impact Motions with Unknown Reaction Forces<br />
Seung-Joon Yi and Daniel D. lee<br />
GRASP Lab, University of Pennsylvania, USA<br />
Byoung-Tak Zhang<br />
BI Lab, Seoul National University, Korea<br />
Dennis Hong<br />
RoMeLa Lab, Virginia Tech, USA<br />
• Humans utilize whole body impact<br />
motions to generate large forces<br />
• Uncertainty in the ensuing reaction<br />
forces can lead robot to instability<br />
• A hierarchical push recovery<br />
controller is used along with<br />
simple robot model to reactively<br />
stabilize the robot against<br />
unknown reaction force<br />
• Implemented and tested on the<br />
DARwIn-OP small humanoid robot