{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:02:33Z","timestamp":1760144553925,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T00:00:00Z","timestamp":1714435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon 2020","award":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"],"award-info":[{"award-number":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"]}]},{"name":"Young Teams project","award":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"],"award-info":[{"award-number":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"]}]},{"name":"DECIDE","award":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"],"award-info":[{"award-number":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"]}]},{"name":"Romanian Ministry of Research, Innovation, and Digitization","award":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"],"award-info":[{"award-number":["871295","PN-III-P1-1.1-TE-2019-1956","57\/14.11.2022"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Consider a drone that aims to find an unknown number of static targets at unknown positions as quickly as possible. A multi-target particle filter uses imperfect measurements of the target positions to update an intensity function that represents the expected number of targets. We propose a novel receding-horizon planner that selects the next position of the drone by maximizing an objective that combines exploration and target refinement. Confidently localized targets are saved and removed from consideration along with their future measurements. A controller with an obstacle-avoidance component is used to reach the desired waypoints. We demonstrate the performance of our approach through a series of simulations as well as via a real-robot experiment in which a Parrot Mambo drone searches from a constant altitude for targets located on the floor. Target measurements are obtained on-board the drone using segmentation in the camera image, while planning is done off-board. The sensor model is adapted to the application. Both in the simulations and in the experiments, the novel framework works better than the lawnmower and active-search baselines.<\/jats:p>","DOI":"10.3390\/s24092868","type":"journal-article","created":{"date-parts":[[2024,4,30]],"date-time":"2024-04-30T08:14:31Z","timestamp":1714464871000},"page":"2868","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Exploration-Based Planning for Multiple-Target Search with Real-Drone Results"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0250-0132","authenticated-orcid":false,"given":"Bilal","family":"Yousuf","sequence":"first","affiliation":[{"name":"Department of Automation, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4539-7876","authenticated-orcid":false,"given":"Zs\u00f3fia","family":"Lendek","sequence":"additional","affiliation":[{"name":"Department of Automation, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucian","family":"Bu\u015foniu","sequence":"additional","affiliation":[{"name":"Department of Automation, Technical University of Cluj-Napoca, Memorandumului 28, 400114 Cluj-Napoca, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,4,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Pallin, M., Rashid, J., and \u00d6gren, P. (2021, January 25\u201327). Formulation and Solution of the Multi-agent Concurrent Search and Rescue Problem. Proceedings of the IEEE International Symposium on Safety, Security, and Rescue Robotics, New York, NY, USA.","DOI":"10.1109\/SSRR53300.2021.9597685"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"847","DOI":"10.1109\/TCNS.2020.3038843","article-title":"A Cooperative Multiagent Probabilistic Framework for Search and Track Missions","volume":"8","author":"Papaioannou","year":"2021","journal-title":"IEEE Trans. Control Netw. Syst."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2405","DOI":"10.1016\/j.ifacol.2020.12.2607","article-title":"Sensor-based Exploration of an Unknown Area with Multiple Mobile Agents","volume":"53","author":"Olcay","year":"2020","journal-title":"IFAC-PapersOnLine"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.1109\/TAES.2005.1561884","article-title":"Sequential Monte Carlo Methods for Multitarget Filtering with Random Finite Sets","volume":"41","author":"Vo","year":"2005","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1007\/s10514-019-09840-9","article-title":"Distributed Multi-Target Search and Tracking Using the PHD filter","volume":"44","author":"Dames","year":"2020","journal-title":"Auton. Robot."},{"key":"ref_6","first-page":"51","article-title":"Active Control Strategies for Discovering and Localizing Devices with Range-Only Sensors","volume":"Volume 107","author":"Charrow","year":"2014","journal-title":"Algorithmic Foundations of Robotics XI"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"3123","DOI":"10.1109\/TCYB.2020.3022952","article-title":"Motion Control for Autonomous Heterogeneous Multiagent Area Search in Uncertain Conditions","volume":"52","year":"2022","journal-title":"IEEE Trans. Cybern."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.ifacol.2021.10.450","article-title":"Movement stabilization of the Parrot Mambo quadcopter along a given trajectory based on PID controllers","volume":"54","author":"Trenev","year":"2021","journal-title":"IFAC-Papers Online"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"144","DOI":"10.3389\/fnbot.2021.753052","article-title":"Multi-Target Coordinated Search Algorithm for Swarm Robotics Considering Practical Constraints","volume":"15","author":"Zhou","year":"2021","journal-title":"Front. Neurorobot."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1016\/j.robot.2019.01.017","article-title":"Efficient decision-making for multiagent target searching and occupancy in an unknown environment","volume":"114","author":"Yan","year":"2019","journal-title":"Robot. Auton. Syst."},{"key":"ref_11","unstructured":"Wang, L., Su, F., Zhu, H., and Shen, L. (2010, January 27\u201329). Active sensing based cooperative target tracking using UAVs in an urban area. Proceedings of the 2010 2nd International Conference on Advanced Computer Control, Shenyang, China."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1007\/s10514-012-9298-8","article-title":"A comparison of path planning strategies for autonomous exploration and mapping of unknown environments","volume":"33","author":"Gil","year":"2012","journal-title":"Auton. Robot."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Dang, T., Khattak, S., Mascarich, F., and Alexis, K. (2019, January 2\u20136). Explore Locally, Plan Globally: A Path Planning Framework for Autonomous Robotic Exploration in Subterranean Environments. Proceedings of the 19th International Conference on Advanced Robotics, Belo Horizonte, Brazil.","DOI":"10.1109\/ICAR46387.2019.8981594"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"445","DOI":"10.1007\/s10846-017-0740-1","article-title":"A Real-Time Path-Planning Algorithm based on Receding Horizon Techniques","volume":"91","author":"Murillo","year":"2018","journal-title":"J. Intellegent Robot. Syst."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1007\/s10514-016-9610-0","article-title":"Receding horizon path planning for 3D exploration and surface inspection","volume":"42","author":"Bircher","year":"2018","journal-title":"Auton. Robot."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"4579","DOI":"10.1109\/TSMC.2019.2943822","article-title":"Tracking Controllers to Chase a Target Using Multiple Autonomous Underwater Vehicles Measuring the Sound Emitted From the Target","volume":"51","author":"Kim","year":"2021","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tyagi, P., Kumar, Y., and Sujit, P.B. (2021, January 15\u201318). NMPC-based UAV 3D Target Tracking In The Presence of Obstacles and Visibility Constraints. Proceedings of the International Conference on Unmanned Aircraft Systems, Athens, Greece.","DOI":"10.1109\/ICUAS51884.2021.9476710"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1540","DOI":"10.1177\/0278364917709507","article-title":"Detecting, localizing, and tracking an Unknown Number of Moving Targets Using a Team of Mobile Robots","volume":"36","author":"Dames","year":"2017","journal-title":"Int. J. Robot. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"2432","DOI":"10.1109\/TCYB.2014.2309898","article-title":"Hierarchical Heuristic Search Using a Gaussian Mixture Model for UAV Coverage Planning","volume":"44","author":"Lin","year":"2014","journal-title":"IEEE Trans. Cybern."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"107398","DOI":"10.1016\/j.engappai.2023.107398","article-title":"Multi-mode filter target tracking method for mobile robot using multi-agent reinforcement learning","volume":"127","author":"Li","year":"2024","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"8354","DOI":"10.1109\/TVT.2023.3245120","article-title":"Multi-UAV Cooperative Search Based on Reinforcement Learning with a Digital Twin Driven Training Framework","volume":"72","author":"Shen","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.dt.2022.09.014","article-title":"Cooperative multi-target hunting by unmanned surface vehicles based on multi-agent reinforcement learning","volume":"29","author":"Xia","year":"2023","journal-title":"Def. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"120643","DOI":"10.1016\/j.eswa.2023.120643","article-title":"A multi-agent reinforcement learning algorithm with the action preference selection strategy for massive target cooperative search mission planning","volume":"231","author":"Wang","year":"2023","journal-title":"Expert Syst. Appl."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Xiao, J., Tan, Y.X.M., Zhou, X., and Feroskhan, M. (2023, January 5\u20136). Learning Collaborative Multi-Target Search for a Visual Drone Swarm. Proceedings of the Preprints of IEEE Conference on Artificial Intelligence, Santa Clara, CA, USA.","DOI":"10.1109\/CAI54212.2023.00012"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"4887","DOI":"10.1007\/s40747-023-00985-w","article-title":"Cooperative multi-agent target searching: A deep reinforcement learning approach based on parallel hindsight experience replay","volume":"9","author":"Zhou","year":"2023","journal-title":"Complex Intell. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Barouch, M., Irad, B.G., and Evgeny, K. (2022). Detection of Static and Mobile Targets by an Autonomous Agent with Deep Q-Learning Abilities. Entropy, 24.","DOI":"10.3390\/e24081168"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Guangcheng, W., Fenglin, W., Yu, J., Minghao, Z., Kai, W., and Hong, Q. (2022). A Multi-AUV Maritime Target Search Method for Moving and Invisible Objects Based on Multi-Agent Deep Reinforcement Learning. Sensors, 22.","DOI":"10.3390\/s22218562"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1302898","DOI":"10.3389\/fnbot.2023.1302898","article-title":"Multi-UAV simultaneous target assignment and path planning based on deep reinforcement learning in dynamic multiple obstacles environments","volume":"17","author":"Kong","year":"2024","journal-title":"Front. Neurorobotics"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wenshan, W., Guoyin, Z., Qingan, D., Dan, L., Yingnan, Z., Sizhao, L., and Dapeng, L. (2023). Multiple Unmanned Aerial Vehicle Autonomous Path Planning Algorithm Based on Whale-Inspired Deep Q-Network. Drones, 7.","DOI":"10.3390\/drones7090572"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chen, J., and Dames, P. (2022). Active Multi-Target Search Using Distributed Thompson Sampling. Tech. Rep. Res. Sq.","DOI":"10.21203\/rs.3.rs-1849567\/v1"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Shirsat, A., and Berman, S. (19\u201321, January 11\u201315). Decentralized Multi-target Tracking with Multiple Quadrotors using a PHD Filter. Proceedings of the AIAA Scitech 2021 Forum, Virtual.","DOI":"10.2514\/6.2021-1583"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Chen, J., and Dames, P. (2020\u201324, January 24). Collision-Free Distributed Multi-Target Tracking Using Teams of Mobile Robots with Localization Uncertainty. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, NV, USA.","DOI":"10.1109\/IROS45743.2020.9341126"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"850","DOI":"10.1109\/TASE.2015.2425212","article-title":"Autonomous Localization of an Unknown Number of Targets without Data Association Using Teams of Mobile Sensors","volume":"12","author":"Dames","year":"2015","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"119609","DOI":"10.1109\/ACCESS.2020.2986492","article-title":"Improved GSO Algorithms and Their Applications in Multi-Target Detection and Tracking Field","volume":"8","author":"Xu","year":"2020","journal-title":"IEEE Access"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"2122","DOI":"10.1109\/TASE.2021.3073938","article-title":"GM-PHD Filter for Searching and Tracking an Unknown Number of Targets with a Mobile Sensor with Limited FOV","volume":"19","author":"Sung","year":"2022","journal-title":"IEEE Trans. Autom. Sci. Eng."},{"key":"ref_36","unstructured":"Ke, C., Lei, C., and Wei, Y. (2022, January 21\u201324). Multi-Sensor Control for Jointly Searching and Tracking Multi-Target Using the Poisson Multi-Bernoulli Mixture. Proceedings of the 11th International Conference on Control, Automation and Information Sciences, Hanoi, Vietnam."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2771","DOI":"10.1109\/TAES.2021.3061802","article-title":"Sensor Management for Search and Track Using the Poisson Multi-Bernoulli Mixture Filter","volume":"57","author":"Per","year":"2021","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"123938","DOI":"10.1109\/ACCESS.2023.3329063","article-title":"Infrared Small Target Tracking Based on OSTrack Model","volume":"11","author":"Shan","year":"2023","journal-title":"IEEE Access"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"43472","DOI":"10.1109\/ACCESS.2023.3269758","article-title":"Radio Frequency Signal Strength Based multi-target Tracking with Robust Path Planning","volume":"11","author":"Tindall","year":"2023","journal-title":"IEEE Access"},{"key":"ref_40","unstructured":"Arkin, R.C., and Diaz, J. (2002, January 3\u20135). Line-of-sight constrained exploration for reactive multiagent robotic teams. Proceedings of the 7th International Workshop on Advanced Motion Control, Maribor, Slovenia."},{"key":"ref_41","unstructured":"Bourgault, F., Makarenko, A.A., Williams, S.B., Grocholsky, B., and Durrant-Whyte, H.F. (October, January 30). Information-based adaptive robotic exploration. Proceedings of the IEEE\/RSJ International Conference on Intelligent Robots and Systems, Lausanne, Switzerland."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"129","DOI":"10.1109\/LRA.2018.2881296","article-title":"Resilient Active Target Tracking with Multiple Robots","volume":"4","author":"Lifeng","year":"2019","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"6554","DOI":"10.1109\/TSP.2014.2364014","article-title":"Labeled Random Finite Sets and the Bayes Multi-Target Tracking Filter","volume":"6","author":"Vo","year":"2014","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"4091","DOI":"10.1109\/TSP.2006.881190","article-title":"The Gaussian Mixture Probability Hypothesis Density Filter","volume":"54","author":"Vo","year":"2006","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1433","DOI":"10.1109\/TSP.2015.2393843","article-title":"Bayesian Multi-Target Tracking with Merged Measurements Using Labelled Random Finite Sets","volume":"63","author":"Beard","year":"2015","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1207","DOI":"10.1007\/s10514-017-9687-0","article-title":"Competitive target search with multi-agent teams: Symmetric and asymmetric communication constraints","volume":"42","author":"Otte","year":"2018","journal-title":"Auton. Robot."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.ifacol.2022.07.614","article-title":"Exploration-Based Search for an Unknown Number of Targets Using a UAV","volume":"55","author":"Yousuf","year":"2022","journal-title":"IFAC-PapersOnLine"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1017\/S0263574719000900","article-title":"Sensor-based navigation of omnidirectional wheeled robots dealing with both collisions and occlusions","volume":"38","author":"Khelloufi","year":"2020","journal-title":"Robotica"},{"key":"ref_49","unstructured":"Lars, G., and J\u00fcrgen, P. (2011). Nonlinear Model Predictive Control, Springer."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.procs.2020.03.038","article-title":"Obstacle Avoidance Model for UAVs with Joint Target based on Multi-Strategies and Follow-up Vector Field","volume":"170","author":"Zheng","year":"2020","journal-title":"Procedia Comput. Sci."},{"key":"ref_51","first-page":"5980","article-title":"Optimal Control of Multiple Drones for Obstacle Avoidance","volume":"56","author":"Codrean","year":"2023","journal-title":"IFAC-PapersOnLine"},{"key":"ref_52","unstructured":"Maer, V.M. (2020). Design and Reference Solution of an Autonomous Quadcopter Racing Competition. [Master\u2019s Thesis, Technical University of Cluj-Napoca]."},{"key":"ref_53","unstructured":"Milan, S., Vaclav, H., and Roger, B. (2008). Image Processing, Analysis and Machine Vision, Global Engineering. [4th ed.]."},{"key":"ref_54","unstructured":"Jing, Z., Yang, C., Shuai, F., Yu, K., and Wen, C.C. (2017, January 21\u201326). Fast Haze Removal for Nighttime Image Using Maximum Reflectance Prior. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1643","DOI":"10.1109\/TCSVT.2022.3214430","article-title":"Multi-Purpose Oriented Single Nighttime Image Haze Removal Based on Unified Variational Retinex Model","volume":"33","author":"Yun","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Mahler, R. (2007). Statistical Multisource-Multitarget Information Fusion, Artech.","DOI":"10.1201\/9781420053098.ch16"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2868\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:37:15Z","timestamp":1760107035000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/9\/2868"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,4,30]]},"references-count":56,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2024,5]]}},"alternative-id":["s24092868"],"URL":"https:\/\/doi.org\/10.3390\/s24092868","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2024,4,30]]}}}