Opportunistic Landmark Registration for Long Distance Relative Path Following. Pierce, D., Martin, S., & Bevly, D. M. In pages 2560–2573, September, 2017. ![Opportunistic Landmark Registration for Long Distance Relative Path Following [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex A method for long distance path duplication of unmanned ground vehicles using relative position information is presented. The path generation errors that typically accumulate for long distance following scenarios are mitigated by exchanging landmark observations between vehicles. Two main differential GPS techniques are used in the presented approach: Dynamic Base RTK and Time Differenced Carrier Phase. The resulting GPS measurements and landmark observations are fused in a graph-based estimation framework for long distance path duplication. The graph-based formulation reduces implementation complexity and processing requirement. A detailed performance evaluation is presented that shows results from both simulated and experimental data. The landmark registration scheme is implemented using point cloud data from a Velodyne VLP-16 multi-channel LiDAR. Results show improved performance when incorporating landmark observations and that path following errors are bounded with respect to following distance between vehicles. The results also indicate that a low number of landmarks need to be exchanged to achieve the desired performance.
@inproceedings{pierce_opportunistic_2017,
title = {Opportunistic {Landmark} {Registration} for {Long} {Distance} {Relative} {Path} {Following}},
url = {http://www.ion.org/publications/abstract.cfm?jp=p&articleID=15222},
doi = {10.33012/2017.15222},
abstract = {A method for long distance path duplication of unmanned ground vehicles using relative position information is presented. The path generation errors that typically accumulate for long distance following scenarios are mitigated by exchanging landmark observations between vehicles. Two main differential GPS techniques are used in the presented approach: Dynamic Base RTK and Time Differenced Carrier Phase. The resulting GPS measurements and landmark observations are fused in a graph-based estimation framework for long distance path duplication. The graph-based formulation reduces implementation complexity and processing requirement. A detailed performance evaluation is presented that shows results from both simulated and experimental data. The landmark registration scheme is implemented using point cloud data from a Velodyne VLP-16 multi-channel LiDAR. Results show improved performance when incorporating landmark observations and that path following errors are bounded with respect to following distance between vehicles. The results also indicate that a low number of landmarks need to be exchanged to achieve the desired performance.},
language = {en},
urldate = {2024-06-20},
author = {Pierce, Dan and Martin, Scott and Bevly, David M.},
month = sep,
year = {2017},
pages = {2560--2573},
}
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