{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/image-based-guidance-of-autonomous-aircraft","title":"Image-based Guidance of Autonomous Aircraft for Wildfire Surveillance and Prediction","arxiv_id":"1810.02455","date":"2018-10-04","proceeding":null,"authors":["Kyle D. Julian","Mykel J. Kochenderfer"],"abstract":"Small unmanned aircraft can help firefighters combat wildfires by providing\nreal-time surveillance of the growing fires. However, guiding the aircraft\nautonomously given only wildfire images is a challenging problem. This work\nmodels noisy images obtained from on-board cameras and proposes two approaches\nto filtering the wildfire images. The first approach uses a simple Kalman\nfilter to reduce noise and update a belief map in observed areas. The second\napproach uses a particle filter to predict wildfire growth and uses\nobservations to estimate uncertainties relating to wildfire expansion. The\nbelief maps are used to train a deep reinforcement learning controller, which\nlearns a policy to navigate the aircraft to survey the wildfire while avoiding\nflight directly over the fire. Simulation results show that the proposed\ncontrollers precisely guide the aircraft and accurately estimate wildfire\ngrowth, and a study of observation noise demonstrates the robustness of the\nparticle filter approach.","url_abs":"http://arxiv.org/abs/1810.02455v2","url_pdf":"http://arxiv.org/pdf/1810.02455v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"image-based-guidance-of-autonomous-aircraft","repo_url":"https://github.com/sisl/UAV_Wildfire_Monitoring","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"deep-reinforcement-learning","task_name":"Deep Reinforcement Learning"},{"task_slug":"navigate","task_name":"Navigate"},{"task_slug":"reinforcement-learning","task_name":"Reinforcement Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=1810.02455","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}