A Lifelong Learning Approach to Mobile Robot Navigation

This letter presents a self-improving lifelong learning framework for a mobile robot navigating in different environments. Classical static navigation methods require environment-specific in-situ system adjustment, e.g., from human experts, or may repeat their mistakes regardless of how many times t...

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Veröffentlicht in:	IEEE robotics and automation letters Jg. 6; H. 2; S. 1090 - 1096
Hauptverfasser:	Liu, Bo, Xiao, Xuesu, Stone, Peter
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.04.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	autonomous vehicle navigation Computation imitation learning Lifelong learning machine learning for robot control Mobile robots Motion and path planning Navigation Optimization Robot sensing systems Robots sensorimotor learning Task analysis Training Tuning
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
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