Lei et al., 2022 - Google Patents
Deep learning-based complete coverage path planning with re-joint and obstacle fusion paradigmLei et al., 2022
View HTML- Document ID
- 10606853757038179059
- Author
- Lei T
- Luo C
- Jan G
- Bi Z
- Publication year
- Publication venue
- Frontiers in Robotics and AI
External Links
Snippet
With the introduction of autonomy into the precision agriculture process, environmental exploration, disaster response, and other fields, one of the global demands is to navigate autonomous vehicles to completely cover entire unknown environments. In the previous …
- 230000004927 fusion 0 title abstract description 14
Classifications
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- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0255—Control of position or course in two dimensions specially adapted to land vehicles using acoustic signals, e.g. ultra-sonic singals
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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- G05D1/0231—Control of position or course in two dimensions specially adapted to land vehicles using optical position detecting means
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- G—PHYSICS
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
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