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Title

Integrating autonomous aerial scouting with autonomous ground actuation to reduce chemical pollution on crop soil

AuthorsConesa-Muñoz, Jesús ; Valente, João; Cerro, Jaime del ; Barrientos, Antonio ; Ribeiro Seijas, Ángela
KeywordsCollaborative inspection
Intervention mission
Aerial fleet
Ground fleet
Autonomous fleet
Site-specific weed treatment
Precision agriculture
Issue Date20-Nov-2015
PublisherSpringer
CitationSecond Iberian Robotics Conference (ROBOT 2015): 177 (2015)
AbstractMany environmental problems cover large areas, often in rough ter-rain constrained by natural obstacles, which makes intervention difficult. New technologies, such as unmanned aerial units, may help to address this issue. Due to their suitability to access and easily cover large areas, unmanned aerial units may be used to inspect the terrain and make a first assessment of the affected areas; however, these platforms do not currently have the capability to imple-ment intervention. This paper proposes integrating autonomous aerial inspection with ground intervention to address environmental problems. Aerial units may be used to easily obtain relevant data about the environment, and ground units may use this information to perform the intervention more efficiently. Furthermore, an overall system to manage these combined missions, com-posed of aerial inspections and ground interventions performed by autonomous robots, is proposed and implemented. The approach was tested on an agricultural scenario, in which the weeds in a crop had to be killed by spraying herbicide on them. The scenario was ad-dressed using a real mixed fleet composed of drones and tractors. The drones were used to inspect the field and to detect weeds and to provide the tractors the exact coordinates to only spray the weeds. This aerial and ground mission col-laboration may save a large amount of herbicide and hence significantly reduce the environmental pollution and the treatment cost, considering the results of several research works that conclude that actual extensive crops are affected by less than a 40% of weed in the worst cases.
DescriptionAccepted English written contributions will be published at Springer Series in Advances in Intelligent Systems and Computing
Publisher version (URL)http://www.springer.com/series/11156
URIhttp://hdl.handle.net/10261/125414
Appears in Collections:(CAR) Comunicaciones congresos
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