Integrating Autonomous Aerial Scouting with Autonomous Ground Actuation to Reduce Chemical Pollution on Crop Soil [chapter]

Jesús Conesa-Muñoz, João Valente, Jaime del Cerro, Antonio Barrientos, Ángela Ribeiro
2015 Advances in Intelligent Systems and Computing  
Many environmental problems cover large areas, often in rough terrain 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 implement intervention. This paper
more » ... es 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, composed 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 addressed 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 collaboration 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 Keywords: collaborative inspection and intervention mission, aerial and ground fleet, autonomous fleet, site-specific weed treatment, precision agriculture
doi:10.1007/978-3-319-27149-1_4 fatcat:euufng2lrnaoxkwbhokf6wwmcy