Towards stratified model-based environmental visual perception for humanoid robots

2011 ◽  
Vol 32 (16) ◽  
pp. 2254-2260 ◽  
Author(s):  
D. Gonzalez-Aguirre ◽  
T. Asfour ◽  
R. Dillmann
Keyword(s):  
Visual Perception ◽  
Humanoid Robots ◽  
Model Based ◽  
Stratified Model

Design of Emotion Expressing Behavior Based on LMA for Aerial Robot

2014 ◽  
Vol 494-495 ◽  
pp. 1170-1174
Author(s):  
Qing Ji Gao ◽  
Meng Li ◽  
Dan Dan Hu ◽  
Wei Hao
Keyword(s):  
Movement Analysis ◽  
Humanoid Robots ◽  
Body Language ◽  
Laban Movement Analysis ◽  
Model Based ◽  
Express Emotion ◽  
Aerial Robot ◽  
Behavior Based ◽  
Movement Parameters ◽  
Emotion Space

The non-humanoid robots can express emotion by imitating the humans body language with different paths. The movement parameters effecting the Laban Effort Factors can be got by parameterizing the trajectory with using Laban Movement Analysis (LMA) Theory. Then, the emotion expressing model based on the trajectory of aerial robot is established by mapping the Effort Factors to the PAD emotion space. The simulation demonstrates the validity of the model.

Active Visual Perception for Humanoid Robots

2015 ◽  
Vol 12 (01) ◽  
pp. 1550009 ◽  
Author(s):  
Francisco Martín ◽  
Carlos E. Agüero ◽  
José M. Cañas
Keyword(s):  
Visual Perception ◽  
Visual Attention ◽  
Visual Memory ◽  
Humanoid Robot ◽  
Partial Information ◽  
Internal Representation ◽  
Humanoid Robots ◽  
Software Components ◽  
Perception System ◽  
Mobile Cameras

Robots detect and keep track of relevant objects in their environment to accomplish some tasks. Many of them are equipped with mobile cameras as the main sensors, process the images and maintain an internal representation of the detected objects. We propose a novel active visual memory that moves the camera to detect objects in robot's surroundings and tracks their positions. This visual memory is based on a combination of multi-modal filters that efficiently integrates partial information. The visual attention subsystem is distributed among the software components in charge of detecting relevant objects. We demonstrate the efficiency and robustness of this perception system in a real humanoid robot participating in the RoboCup SPL competition.

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