148195 20260217205519.0 doi 10.1016/j.robot.2024.104892 sideral 141706 ART-2024-141706 eng Marchukov, Yaroslav Occupation-aware planning method for robotic monitoring missions in dynamic environments 2024 Access copy available to the general public Unrestricted This paper presents a method for robotic monitoring missions in the presence of moving obstacles. Although the scenario map is known, the robot lacks information about the movement of dynamic obstacles during the monitoring mission. Numerous local planners have been developed in recent years for navigating highly dynamic environments. However, the absence of a global planner for these environments can result in unavoidable collisions or the inability to successfully complete missions in densely populated areas, such as a scenario monitoring in our case. This work addresses the development and evaluation of a global planner, (Monitoring Avoiding Dynamic Areas), aimed at enhancing the deployment of robots in such challenging conditions. The robot plans and executes the mission using the proposed two-step approach. The first step involves selecting the observation goal based on the environment’s distribution and estimated monitoring costs. In the second step, the robot identifies areas with moving obstacles and obtains paths avoiding densely occupied dynamic regions based on their occupation. Quantitative and qualitative results based on simulations and on real-world experimentation, confirm that the proposed method allows the robot to effectively monitor most of the environment while avoiding densely occupied dynamic areas. info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ 5.2 2024 AUTOMATION & CONTROL SYSTEMS 18 / 89 = 0.202 2024 Q1 T1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 51 / 204 = 0.25 2024 Q1 T1 ROBOTICS 13 / 48 = 0.271 2024 Q2 T1 1.168 2024 Computer Science Applications 2024 Q1 Software 2024 Q1 Mathematics (miscellaneous) 2024 Q1 Control and Systems Engineering 2024 Q1 9.9 2024 info:eu-repo/semantics/article info:eu-repo/semantics/submittedVersion Montano, Luis Universidad de Zaragoza (orcid)0000-0002-0449-2300 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 185 (2024), 104892 [17 pp.] Robot. auton. syst. ROBOTICS AND AUTONOMOUS SYSTEMS 0921-8890 The code used for this research https://github.com/yamarle/mada.git 2180319 http://zaguan.unizar.es/record/148195/files/texto_completo.pdf Preprint 2388666 http://zaguan.unizar.es/record/148195/files/texto_completo.jpg?subformat=icon icon Preprint oai:zaguan.unizar.es:148195 articulos driver 2026-02-17-20:27:59 ARTICLE