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| Autore: |
Kaul Lukas Sebastian
|
| Titolo: |
Human-Inspired Balancing and Recovery Stepping for Humanoid Robots
|
| Pubblicazione: | KIT Scientific Publishing, 2019 |
| Descrizione fisica: | 1 online resource (X, 235 p. p.) |
| Soggetto non controllato: | Balancieren |
| Balancing | |
| Control systems | |
| Humanoid robotics | |
| Humanoide Robotik | |
| Machine learning | |
| Maschinelles Lernen | |
| Optimierung | |
| Optimization | |
| Regelungstechnik | |
| Sommario/riassunto: | Robustly maintaining balance on two legs is an important challenge for humanoid robots. The work presented in this book represents a contribution to this area. It investigates efficient methods for the decision-making from internal sensors about whether and where to step, several improvements to efficient whole-body postural balancing methods, and proposes and evaluates a novel method for efficient recovery step generation, leveraging human examples and simulation-based reinforcement learning. |
| Titolo autorizzato: | Human-Inspired Balancing and Recovery Stepping for Humanoid Robots ![]() |
| ISBN: | 1000091605 |
| Formato: | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione: | Inglese |
| Record Nr.: | 9910346946503321 |
| Lo trovi qui: | Univ. Federico II |
| Opac: | Controlla la disponibilità qui |