A Top-Down and Bottom-Up Visual Attention Model for Humanoid Object Approaching and Obstacle Avoidance
| Autor: | Hendry Ferreira Chame, Christine Chevallereau |
|---|---|
| Přispěvatelé: | Robotique, Institut de Recherche en Communications et en Cybernétique de Nantes (IRCCyN), Mines Nantes (Mines Nantes)-École Centrale de Nantes (ECN)-Ecole Polytechnique de l'Université de Nantes (EPUN), Université de Nantes (UN)-Université de Nantes (UN)-PRES Université Nantes Angers Le Mans (UNAM)-Centre National de la Recherche Scientifique (CNRS)-Mines Nantes (Mines Nantes)-École Centrale de Nantes (ECN)-Ecole Polytechnique de l'Université de Nantes (EPUN), Université de Nantes (UN)-Université de Nantes (UN)-PRES Université Nantes Angers Le Mans (UNAM)-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2016 |
| Předmět: |
Image segmentation
0209 industrial biotechnology Computer science business.industry Representation (systemics) 02 engineering and technology Visual servoing Object (philosophy) [SPI.AUTO]Engineering Sciences [physics]/Automatic Task (project management) Visualization 020901 industrial engineering & automation Robot sensing systems Encoding Obstacle avoidance 0202 electrical engineering electronic engineering information engineering Legged locomotion Robot 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Humanoid robot |
| Zdroj: | 2016 XIII Latin American Robotics Symposium and IV Brazilian Robotics Symposium (LARS/SBR) 2016 XIII Latin American Robotics Symposium and IV Brazilian Robotics Symposium (LARS/SBR), Oct 2016, Recife, Brazil. ⟨10.1109/LARS-SBR.2016.12⟩ |
| DOI: | 10.1109/lars-sbr.2016.12 |
| Popis: | International audience; Most of the research on humanoid walk tasks has considered a global representation of the scene that frequently relies on external sensors. This is detrimental to the autonomy and the reactivity of the agent under unknown or changing scenarios. Ego-centric localization has been less explored, and the works considering on-board acquisitions have mostly dealt with tasks under controlled scenarios where the path to the object is cleared from obstacles. In this work a behavior-based control scheme is proposed, so the robot Nao can approach and position in relation to a given face of an object, while avoiding obstacles. For this, the solution relies on top-down (color-based) and bottom-up (optic-flow-based) visual features, and proprioceptive information registered on-board. The model is decentralized and exploits the emergent aspect of behavior from the independent contribution of a walk and a look-at task. An embodied visual encoding approach is proposed to support the arbitration between competing behavioral modes. |
| Databáze: | OpenAIRE |
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