Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user’s threshold, using the Geometric Dilution of Precision (GDoP).

On-line Optimal Ranging Sensor Deployment for Robotic Exploration / Santoro, Luca; Brunelli, Davide; Fontanelli, Daniele. - In: IEEE SENSORS JOURNAL. - ISSN 1530-437X. - 2022, 22:6(2022), pp. 5417-5426. [10.1109/JSEN.2021.3120889]

On-line Optimal Ranging Sensor Deployment for Robotic Exploration

Santoro, Luca;Brunelli, Davide;Fontanelli, Daniele
2022-01-01

Abstract

Navigation in an unknown environment without any preexisting positioning infrastructure has always been hard for mobile robots. This paper presents a self-deployable ultra wideband UWB infrastructure by mobile agents, that permits a dynamic placement and runtime extension of UWB anchors infrastructure while the robot explores the new environment. We provide a detailed analysis of the uncertainty of the positioning system while the UWB infrastructure grows. Moreover, we developed a genetic algorithm that minimizes the deployment of new anchors, saving energy and resources on the mobile robot and maximizing the time of the mission. Although the presented approach is general for any class of mobile system, we run simulations and experiments with indoor drones. Results demonstrate that maximum positioning uncertainty is always controlled under the user’s threshold, using the Geometric Dilution of Precision (GDoP).
2022
6
Santoro, Luca; Brunelli, Davide; Fontanelli, Daniele
On-line Optimal Ranging Sensor Deployment for Robotic Exploration / Santoro, Luca; Brunelli, Davide; Fontanelli, Daniele. - In: IEEE SENSORS JOURNAL. - ISSN 1530-437X. - 2022, 22:6(2022), pp. 5417-5426. [10.1109/JSEN.2021.3120889]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/320371
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