SACSoN: Scalable Autonomous Control for Social Navigation

Machine learning provides a powerful tool for building socially compliant robotic systems that go beyond simple predictive models of human behavior. By observing and understanding human interactions from past experiences, learning can enable effective social navigation behaviors directly from data....

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Vydané v:	IEEE robotics and automation letters Ročník 9; číslo 1; s. 49 - 56
Hlavní autori:	Hirose, Noriaki, Shah, Dhruv, Sridhar, Ajay, Levine, Sergey
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Behavioral sciences Data Sets for Robot Learning Datasets Human behavior Machine learning Machine Learning for Robot Control Navigation Pedestrians Perturbation Perturbation methods Policies Prediction models Predictive models Robot control Robot learning Robots social navigation Social robots Visual observation Visualization
ISSN:	2377-3766, 2377-3766
On-line prístup:	Získať plný text
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