Single Plant Fertilization Using a Robotic Platform in an Organic Cropping Environment
Constantino Valero,
Anne Krus,
Christyan Cruz Ulloa,
Antonio Barrientos,
Juan José Ramírez-Montoro,
Jaime del Cerro,
Pablo Guillén
Affiliations
Constantino Valero
LPF_Tagralia, Departamento de Ingeniería Agroforestal, ETSI Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Av. Puerta Hierro 2, 28040 Madrid, Spain
Anne Krus
LPF_Tagralia, Departamento de Ingeniería Agroforestal, ETSI Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Av. Puerta Hierro 2, 28040 Madrid, Spain
Christyan Cruz Ulloa
Centre for Automation and Robotics (CSIC-UPM), Consejo Superior de Investigaciones Científicas—Universidad Politécnica de Madrid, José Gutiérrez Abascal 2, 28006 Madrid, Spain
Antonio Barrientos
Centre for Automation and Robotics (CSIC-UPM), Consejo Superior de Investigaciones Científicas—Universidad Politécnica de Madrid, José Gutiérrez Abascal 2, 28006 Madrid, Spain
Juan José Ramírez-Montoro
LPF_Tagralia, Departamento de Ingeniería Agroforestal, ETSI Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Av. Puerta Hierro 2, 28040 Madrid, Spain
Jaime del Cerro
Centre for Automation and Robotics (CSIC-UPM), Consejo Superior de Investigaciones Científicas—Universidad Politécnica de Madrid, José Gutiérrez Abascal 2, 28006 Madrid, Spain
Pablo Guillén
LPF_Tagralia, Departamento de Ingeniería Agroforestal, ETSI Agronómica, Alimentaria y de Biosistemas, Universidad Politécnica de Madrid, Av. Puerta Hierro 2, 28040 Madrid, Spain
The growing demand for organically produced vegetables requires the adoption of new cropping systems such as strip-cropping. To counteract the additional labour mixed cropping entails, automation and robotics play a key role. This research focuses on the development of a proof-of-concept platform that combines optical sensors and an actuation system for targeted precision fertilization that encircles selected plants rather than a local field area. Two sensor types are used for the detection of a fertilisation need: a multispectral camera and light detection and ranging (LiDAR) devices in order to acquire information on plant health status and three-dimensional characterisation. Specific algorithms were developed to more accurately detect a change in fertilization need. An analysis of their results yields a prescription map for automatic fertilisation through a robotic arm. The relative location of the platform within the prescription map is essential for the correct application of fertilizers, and is acquired through live comparison of a LiDAR pushbroom with the known 3D world model. The geometry of each single plant is taken into account for the application of the sprayed fertiliser. This resulted in a reliable method for the detection of delayed growth and prototype localization within a changing natural environment without relying on external markers.