2026-06-01T01:21:29Zhttps://riuma.uma.es/rest/oai/request

oai:riuma.uma.es:10630/341672026-02-03T10:57:04Zcom_10630_2254col_10630_37953

00925njm 22002777a 4500 dc Polvara, Ricardo author Fernández-Carmona, Manuel author Neumann, Gerhard author Hanheide, Marc author 2020 Automated exploration is one of the most relevant applications for autonomous robots. In this letter, we propose a novel online coverage algorithm called Next-Best-Sense (NBS), an extension of the Next-Best-View class of exploration algorithms which optimizes the exploration task balancing multiple criteria. NBS is applied to the problem of localizing all Radio Frequency Identification (RFID) tags with a mobile robot. We cast this problem as a coverage planning problem by defining a basic sensing operation - a scan with the RFID reader - as the field of “view” of the sensor. NBS evaluates candidate locations with a global utility function which combines utility values for travel distance, information gain, sensing time, battery status and RFID information gain, generalizing the use of Multi-Criteria Decision Making. We developed an RFID reader and tag model in the Gazebo simulator for validation. Experiments performed both in simulation and with a robot suggest that our NBS approach can successfully localize all the RFID tags while minimizing navigation metrics, such sensing operations, total traveling distance and battery consumption. https://hdl.handle.net/10630/34167 10.1109/LRA.2020.3001539 Robótica Radiofrecuencia Next-Best-Sense: a multi-criteria robotic exploration strategy for RFID tags discovery