Visual Terrain Classification Methods for Mobile Robots Using Hybrid Coding Architecture

Visual terrain classification can provide crucial and important information for motion control and autonomous navigation for mobile robots in complex terrain environment, becoming an important but challenging task. This paper uses a novel hybrid coding architecture, Deep Filter Banks (DFB), combinin...

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Veröffentlicht in:	2019 IEEE 4th International Conference on Image, Vision and Computing (ICIVC) S. 17 - 22
Hauptverfasser:	Wu, Hang, Zhang, Wenchang, Li, Boyang, Sun, Yucao, Duan, Deguang, Chen, Ping
Format:	Tagungsbericht
Sprache:	Englisch
Veröffentlicht:	IEEE 01.07.2019
Schlagworte:	arc-legged mobile robot Autonomous robots Benchmark testing Computer architecture deep filter banks Encoding Filter banks fisher vector Mobile robots Motion control terrain dataset Vectors Videos visual terrain classification Visualization
Online-Zugang:	Volltext
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