Predictive Probability Density Mapping for Search and Rescue Using an Agent-Based Approach With Sparse Data

Predictive Probability Density Mapping for Search and Rescue Using an Agent-Based Approach With Sparse Data

Predicting the location where a lost person could be found is crucial for search and rescue operations with limited resources. To improve the precision and efficiency of these predictions, simulated agents can be created to emulate the behavior of the lost person. Within this study, we introduce an...

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Bibliographic Details
Main Authors: Jan-Hendrik Ewers, David Anderson, Douglas Thomson
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Search and rescue
probability distribution map
agent
Monte-Carlo
Gaussian process
predictive
Online Access:https://ieeexplore.ieee.org/document/10948401/
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https://ieeexplore.ieee.org/document/10948401/

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