TY - JOUR
T1 - Camera-based mapping in search-and-rescue via flying and ground robot teams
AU - Esteves Henriques, Bernardo
AU - Baglioni, Mirko
AU - Jamshidnejad, Anahita
PY - 2024
Y1 - 2024
N2 - Search and rescue (SaR) is challenging, due to the unknown environmental situation after disasters occur. Robotics has become indispensable for precise mapping of the environment and for locating the victims. Combining flying and ground robots more effectively serves this purpose, due to their complementary features in terms of viewpoint and maneuvering. To this end, a novel, cost-effective framework for mapping unknown environments is introduced that leverages You Only Look Once and video streams transmitted by a ground and a flying robot. The integrated mapping approach is for performing three crucial SaR tasks: localizing the victims, i.e., determining their position in the environment and their body pose, tracking the moving victims, and providing a map of the ground elevation that assists both the ground robot and the SaR crew in navigating the SaR environment. In real-life experiments at the CyberZoo of the Delft University of Technology, the framework proved very effective and precise for all these tasks, particularly in occluded and complex environments.
AB - Search and rescue (SaR) is challenging, due to the unknown environmental situation after disasters occur. Robotics has become indispensable for precise mapping of the environment and for locating the victims. Combining flying and ground robots more effectively serves this purpose, due to their complementary features in terms of viewpoint and maneuvering. To this end, a novel, cost-effective framework for mapping unknown environments is introduced that leverages You Only Look Once and video streams transmitted by a ground and a flying robot. The integrated mapping approach is for performing three crucial SaR tasks: localizing the victims, i.e., determining their position in the environment and their body pose, tracking the moving victims, and providing a map of the ground elevation that assists both the ground robot and the SaR crew in navigating the SaR environment. In real-life experiments at the CyberZoo of the Delft University of Technology, the framework proved very effective and precise for all these tasks, particularly in occluded and complex environments.
KW - Computer vision
KW - Homography estimation
KW - Object detection
KW - Pose estimation
KW - Search and rescue robotics
KW - State estimation
KW - Terrain mapping
UR - http://www.scopus.com/inward/record.url?scp=85201565564&partnerID=8YFLogxK
U2 - 10.1007/s00138-024-01594-4
DO - 10.1007/s00138-024-01594-4
M3 - Article
AN - SCOPUS:85201565564
SN - 0932-8092
VL - 35
JO - Machine Vision and Applications
JF - Machine Vision and Applications
IS - 5
M1 - 117
ER -