From def4f97ff47131ac0085053887809a174607b385 Mon Sep 17 00:00:00 2001 From: Erik van Sebille Date: Thu, 13 Jun 2024 12:18:22 -0400 Subject: [PATCH] Adding Boulares article --- articles.html | 32 ++++++++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) diff --git a/articles.html b/articles.html index e9210df..5daedba 100644 --- a/articles.html +++ b/articles.html @@ -118,6 +118,38 @@

Peer-reviewed articles using Parcels

+
+
+
+ +
+
+ In the context of real world application, Search and Rescue Missions on the ocean surface remain a complex task due to the large-scale area and the forces of the ocean currents, spreading lost targets and debris in an unpredictable way. In this work, we present a Path Planning Approach to search for a lost target on ocean surface using a swarm of UAVs. The combination of GlobCurrent dataset and a Lagrangian simulator is used to determine where the particles are moved by the ocean currents forces while Deep Q-learning algorithm is applied to learn from their dynamics. The evaluation results of the trained models show that our search strategy is effective and efficient. Over a total search area (red Sea zone), surface of 453422 Km, we have shown that our strategy Search Success Rate is 98.61%, the maximum Search Time to detection is 15 days and the average Search Time to detection is almost 15 h. +
+
+
+
+
+