.png){kind=icon}
返回
Active robotic search for victims using ensemble deep learning techniques
.png){kind=icon}
OA
AI
DOI：10.1088/2632-2153/ad33df.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In recent years, legged quadruped robots have proved to be a valuable support to humans in dealing with search and rescue operations. These robots can move with great ability in complex terrains, unstructured environments or regions with many obstacles. This work employs the quadruped robot A1 Rescue Tasks UPM Robot (ARTU-R) by Unitree, equipped with an RGB-D camera and a lidar, to perform victim searches in post-disaster scenarios. Exploration is done not by following a pre-planned path (as common methods) but by prioritising the areas most likely to harbour victims. To accomplish that task, both indirect search and next best view techniques have been used. When ARTU-R gets inside an unstructured and unknown environment, it selects the next exploration point from a series of candidates. This operation is performed by comparing, for each candidate, the distance to reach it, the unexplored space around it and the probability of a victim being in its vicinity. This probability value is obtained using a Random Forest, which processes the information provided by a convolutional neural network. Unlike other AI techniques, random forests are not black box models; humans can understand their decision-making processes. The system, once integrated, achieves speeds comparable to other state-of-the-art algorithms in terms of exploration, but concerning victim detection, the tests show that the resulting smart exploration generates logical paths-from a human point of view-and that ARTU-R tends to move first to the regions where victims are present.
Keyword:
search and rescue robots
sensing and perception
computer vision
legged robots
ensamble deep learning
random forests
期刊
M
IF:
4.6
论文数:
1.1K
被引数:
3.4K
机构
引用论文
.png){kind=icon}
分享收藏A Kind of Preconditioners Based on Shifted Operators to Solve Three-Dimensional TVFEM Equations
PREAI
分享收藏Clinical activity of the ALK inhibitor LDK378 in advanced, ALK-positive NSCLC.ALK抑制剂LDK378在晚期ALK阳性NSCLC中的临床活性。
PREAI
分享收藏Measurement of the Dichotic Listening Ear Advantage for Intersubject and Interstimulus Comparisons
PREAI
分享收藏Supervised learning for maritime search operations: An artificial intelligence approach to search efficiency evaluation海上搜索操作的监督学习: 搜索效率评估的人工智能方法
OAAI
OAAI分享收藏
查看更多内容