TY - GEN
T1 - Autonomous Target Search in Unknown Dynamic Environments with a Mobile Robot
AU - Huang, Jingtao
AU - Zhang, Lele
AU - Sun, Zhihao
AU - Deng, Fang
N1 - Publisher Copyright:
©2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Autonomous target search is a crucial topic in robotics, with applications in search and rescue, environmental monitoring, and resource exploration. Dynamic changes in the environment undermine the validity of constructed maps and cause frequent planning failures, posing significant challenges to autonomous target search. This paper proposes a novel method to achieve efficient autonomous target search in unknown dynamic environments with a mobile robot. First, we perform topological mapping to obtain structural information and passage traversability status in the environment, addressing the degradation of mapping validity caused by dynamic environmental changes. Second, we design a search planning strategy that balances exploration, inspection, and monitoring, enabling the robot to maintain search efficiency while adapting to unknown environmental changes. Finally, we conduct ROS-Gazebo simulation experiments and compare our method with a state-of-the-art method to demonstrate the superiority of our method in completeness and to verify that it does not incur excessive unnecessary movement due to handling dynamic environments.
AB - Autonomous target search is a crucial topic in robotics, with applications in search and rescue, environmental monitoring, and resource exploration. Dynamic changes in the environment undermine the validity of constructed maps and cause frequent planning failures, posing significant challenges to autonomous target search. This paper proposes a novel method to achieve efficient autonomous target search in unknown dynamic environments with a mobile robot. First, we perform topological mapping to obtain structural information and passage traversability status in the environment, addressing the degradation of mapping validity caused by dynamic environmental changes. Second, we design a search planning strategy that balances exploration, inspection, and monitoring, enabling the robot to maintain search efficiency while adapting to unknown environmental changes. Finally, we conduct ROS-Gazebo simulation experiments and compare our method with a state-of-the-art method to demonstrate the superiority of our method in completeness and to verify that it does not incur excessive unnecessary movement due to handling dynamic environments.
KW - Autonomous Target Search
KW - Mobile Robot
KW - Topological Mapping
KW - Unknown Dynamic Environment
UR - https://www.scopus.com/pages/publications/105033892393
U2 - 10.1109/ACIRS66343.2025.11360867
DO - 10.1109/ACIRS66343.2025.11360867
M3 - Conference contribution
AN - SCOPUS:105033892393
T3 - 2025 10th Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2025
SP - 165
EP - 172
BT - 2025 10th Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th Asia-Pacific Conference on Intelligent Robot Systems, ACIRS 2025
Y2 - 14 November 2025 through 16 November 2025
ER -