European Robotics Symposium 2006
This unique reference represents a cross-section of forefront robotics research, ranging from robotics and systems to learning, autonomy and failure detection, from vision and navigation to localization and mapping, which are based on the papers presented at the 1st European Robotics Symposium (EURO...
保存先:
| 第一著者: | |
|---|---|
| フォーマット: | Livre numérique |
| 言語: | Anglais |
| 出版事項: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| 版: | 1st ed. 2006. |
| シリーズ: | Springer Tracts in Advanced Robotics
22 |
| オンライン･アクセス: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| 注記: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • European Robotics Symposium 2006, Texte imprimé, 9783540326892 |
目次:
- An Ontology of Robotics Science A Multi-Agent System Architecture for Modular Robotic Mobility Aids How to Construct Dense Objects with Self-Reconfigurable Robots In Situ Autonomous Biomechanical Characterization Incremental Learning of Task Sequences with Information- Theoretic Metrics Representation, Recognition and Generation of Actions in the context of Imitation Learning Reduction of Learning Time for Robots Using Automatic State Abstraction Efficient Failure Detection for Mobile Robots Using Mixed-Abstraction Particle Filters Optimization and Fail Safety Analysis of Antagonistic Actuation for pHRI Bilateral Control of Different Order Teleoperators Navigation and planning in an unknown environment using vision and a cognitive map Exploiting Distinguishable Image Features in Robotic Mapping and Localization Image-Based Visual Servoing for Mobile Robots with Catadioptric Camera Multi-knowledge Approach for Mobile Robot Identification of a Changing Environment Robust Monte-Carlo Localization using Adaptive Likelihood Models Metric Localization with Scale-Invariant Visual Features using a Single Perspective Camera