[go: up one dir, main page]

Prinz et al., 2022 - Google Patents

Off-road navigation maps for robotic platforms using convolutional neural networks

Prinz et al., 2022

View PDF
Document ID
11015699063994580021
Author
Prinz R
Bulbul R
Scholz J
Eder M
Steinbauer-Wagner G
Publication year
Publication venue
AGILE: GIScience Series

External Links

Snippet

As part of AMADEE-20, an integrated Mars analog field mission in the Negev Desert in Israel conducted by the Austrian Space Forum, an exploration cascade for the remote sensing of extraterrestrial terrain was implemented. For this purpose, aerial robots were …
Continue reading at agile-giss.copernicus.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in preceding groups
    • G01C21/20—Instruments for performing navigational calculations
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06K—RECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00624—Recognising scenes, i.e. recognition of a whole field of perception; recognising scene-specific objects
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01V—GEOPHYSICS; GRAVITATIONAL MEASUREMENTS; DETECTING MASSES OR OBJECTS
    • G01V1/00—Seismology; Seismic or acoustic prospecting or detecting

Similar Documents

Publication Publication Date Title
Delmerico et al. Active autonomous aerial exploration for ground robot path planning
US9266611B2 (en) Flight path development for remote sensing vehicles in a moving reference frame
Nowakowski et al. Advance reconnaissance of UGV path planning using unmanned aerial vehicle to carry our mission in unknown environment
Stothard et al. Application of UAVs in the mining industry and towards an integrated UAV-AI-MR technology for mine rehabilitation surveillance
Subramanian et al. Integrating computer vision and photogrammetry for autonomous aerial vehicle landing in static environment
Prinz et al. Off-road navigation maps for robotic platforms using convolutional neural networks
Reis et al. Forest robot and datasets for biomass collection
Bakambu et al. Field trial results of planetary rover visual motion estimation in Mars analogue terrain
Didari et al. The AMADEE-20 robotic exploration cascade: an experience report
Galvez-Serna et al. Real-time segmentation of desiccation cracks onboard UAVs for planetary exploration
Paar et al. PRoViScout: a planetary scouting rover demonstrator
Iakovlev et al. Method for searching deployment zones of ground seismic sensors by a heterogeneous group of UAVs in an environment with a complex topography
Sinhababu et al. An efficient obstacle detection scheme for low-altitude UAVs using google maps
Suir et al. Unmanned aircraft systems to support environmental applications within USACE civil works
Kanade et al. CMU strategic computing vision project report: 1984 to 1985
Hutsul et al. Recommendations for planning UAV flight missions for geodata collection
Pisanich et al. Initial efforts toward mission-representative imaging surveys from aerial explorers
Ostler et al. Generating Efficient Sensor Paths for Ground Target Search: A Performance Parameter and GIS-Driven Approach
Stoker et al. Two dogs, new tricks: A two‐rover mission simulation using K9 and FIDO at Black Rock Summit, Nevada
Sheppard et al. Automatic Data Processing for Space Robotics Machine Learning
Mantoani et al. Path planning with far-away obstacles detection under uncertainty
Viswanath et al. Trailblazer: Learning offroad costmaps for long range planning
Shah Heading estimation via Sun sensing for autonomous navigation
Bjelotomic et al. Navigation Method for Ugv on Aerial Elevation Maps for Autonomous Missions in Sandy Deserts
Salhi et al. Leveraging AI and Hybrid Intelligence for Robust Geospatial Data Fusion in Autonomous Terrestrial Navigation.