Sensor Fusion For Avoidance
Sensor Fusion for Avoidance is a computational framework that integrates heterogeneous sensory data from multiple modalities to enhance the accuracy, robustness, and reliability of obstacle detection and avoidance decisions in dynamic environments.
38
Publications
1K
Citations
137
Authors
50
Institutions
Publications per year
2017–2026
18
Parents
38
A hybrid collision avoidance method for mobile robots
D. Fox, Wolfram Burgard, Sebastian Thrun et al. · 2002 · 103 citations
Design and development of orchard autonomous navigation spray system
Shubo Wang, Jianli Song, Peng Qi et al. · Frontiers in Plant Science · 2022 · 53 citations · Full text
Engineering, Agricultural Engineering, Autonomous Systems +17
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University of Bridgeport
Bridgeport, United States
2 h-index
4 publications
160 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
2 publications
122 citations
Sepuluh Nopember Institute of Technology
Surabaya, Indonesia
1 h-index
3 publications
30 citations

University of Tehran
Tehran, Iran
1 h-index
9 publications
1.4K citations
First Affiliated Hospital of Xi'an Jiaotong University
Xi'an, China
1 h-index
3 publications
30 citations

Beihang University
Beijing, China
1 h-index
2 publications
28 citations
Ministry of Agriculture and Rural Affairs
Beijing, China
1 h-index
7 publications
273 citations
Tsinghua University
Beijing, China
1 h-index
1 publications
37 citations
1–8 of 50
2 publications · 29 citations
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Repository · 1 publications · 10 citations
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1 publications · 13 citations
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1 publications · 10 citations
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1 publications · 11 citations
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