3D Map Reconstruction of an Orchard using an Angle-Aware Covering Control Strategy. Issue 32 (2022)

• Record Type: Journal Article
• Authors: Mammarella, Martina; Donati, Cesare; Shimizu, Takumi; Suenaga, Masaya; Comba, Lorenzo; Biglia, Alessandro; Uto, Kuniaki; Hatanaka, Takeshi; Gay, Paolo; Dabbene, Fabrizio
• Is Part Of: IFAC-PapersOnLine. Volume 55:Issue 32(2022)
• Page Start: 271
• Page End: 276
• Publication Date: 2022
• Subjects: Precision farming -- Agricultural robotics -- Autonomous vehicles in agriculture -- Covering control -- Crop modeling; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2022.11.151
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: In the last years, unmanned aerial vehicles are becoming a reality in the context of precision agriculture, mainly for monitoring, patrolling and remote sensing tasks, but also for 3D map reconstruction. In this paper, we present an innovative approach where a fleet of unmanned aerial vehicles is exploited to perform remote sensing tasks over an apple orchard for reconstructing a 3D map of the field, formulating the covering control problem to combine the position of a monitoring target and the viewing angle. Moreover, the objective function of the controller is defined by an importance index, which has been computed from a multi-spectral map of the field, obtained by a preliminary flight, using a semantic interpretation scheme based on a convolutional neural network. This objective function is then updated according to the history of the past coverage states, thus allowing the drones to take situation-adaptive actions. The effectiveness of the proposed covering control strategy has been validated through simulations on a Robot Operating System.