Large-Scale Autonomous Flight With Real-Time Semantic SLAM Under Dense Forest Canopy

Semantic maps represent the environment using a set of semantically meaningful objects. This representation is storage-efficient, less ambiguous, and more informative, thus facilitating large-scale autonomy and the acquisition of actionable information in highly unstructured, GPS-denied environments...

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Veröffentlicht in:	IEEE robotics and automation letters Jg. 7; H. 2; S. 5512 - 5519
Hauptverfasser:	Liu, Xu, Nardari, Guilherme V., Cladera, Fernando, Tao, Yuezhan, Zhou, Alex, Donnelly, Thomas, Qu, Chao, Chen, Steven W., Romero, Roseli A. F., Taylor, Camillo J., Kumar, Vijay
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 01.04.2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Aerial systems: perception and autonomy Autonomous aerial vehicles Autonomous navigation Autonomy Canopies Computational modeling Control stability Data models Drift field robotics Forestry Ground plane Mapping Planning Real time Real-time systems robotics and automation in agriculture and forestry Semantics Simultaneous localization and mapping SLAM Stability analysis Trajectory Unmanned aerial vehicles Unstructured data
ISSN:	2377-3766, 2377-3766
Online-Zugang:	Volltext
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