Precision agriculture has been increasingly recognized for its potential ability to improve agricultural productivity, reduce production cost, and minimize damage to the environment. In this work, the current stage of our research in developing a mobile platform equipped with different sensors for orchard monitoring and sensing is presented. In particular, the mobile platform is conceived to monitor and assess both the geometric and volumetric conditions as well as the health state of the canopy. To do so, different sensors have been integrated and effective data-processing algorithms implemented for a reliable crop monitoring. Experimental tests have been performed allowing to obtain both a precise volume reconstruction of several plants and an NDVI mapping suitable for vegetation state evaluations.

At today, available mechatronics technology allows exploiting smart and precise sensors as well as embedded and effective mechatronic systems for developing (semi-)autonomous robotic platforms able to both navigate in different outdoor environments and implementing Precision Farming techniques. In this work, the experimental outdoor assessment of the performance of a mobile robotic lab, the ByeLab — Bionic eYe Laboratory — is presented and discussed. The ByeLab, developed at the Faculty of Science and Technology of the Free University of Bolzano (I), has been conceived with the aim of creating a (semi-)autonomous robotic system able to sense and monitor the health status of orchards and vineyards. For assessing and measuring the shape and the volume of the canopy, LIDAR technology coupled with ad-hoc developed algorithms have been exploited. To validate the ByeLab different experimental tests have been carried out. In addition to the in-lab and structured environments experimental tests that allowed to tune the algorithms, in this work the assessment of its capabilities — in particular the sensoric system — has been made outdoor controlled environment tests.

Purpose The aim of this paper is the implementation and validation of control and guidance algorithms for unmanned aerial vehicle (UAV) autopilots. Design/methodology/approach The path-following control of the UAV can be separated into different layers: inner loop for pitch and roll attitude control, outer loop on heading, altitude and airspeed control for the waypoints tracking and waypoint navigation. Two control laws are defined: one based on proportional integrative derivative (PID) controllers both for inner and outer loops and one based on the combination of PIDs and an adaptive controller. Findings Good results can be obtained in terms of trajectory tracking (based on waypoints) and of parameter variations. The adaptive control law guarantees smoothing responses and less oscillations and glitches on the control deflections. Practical implications The proposed controllers are easily implementable on-board and are computationally efficient. Originality/value The algorithm validation via hardware in the loop simulations can be used to reduce the platform set-up time and the risk of losing the prototype during the flight tests.

Summary The aim of WEQUAL project (WEb service centre for QUALity multidimensional design and tele-operated monitoring of Green Infrastructures) is the development of a system that is able to support a quick environmental monitoring of riparian areas subjected to the realization of new green infrastructures (GI). The Wequal’s idea is to organize a service center able to manage both the Web Platform and the whole data collection and analysis processes. Through a personal account, the final user (designer, technician, researcher) can get access to the service and requires the evaluation of alternatives GI projects. On the Web Platform, a set of algorithms runs in order to calculate, through automatic procedures, all the ecological criteria required to evaluate a quality environmental index that describes the eco-morphological value of the monitored riparian areas. For this aim, the WEQUI index was developed, which uses 15 indicators that are easy to monitor. In this paper, the approach for environmental data collection and the procedures to perform the automatic assessment of two of the ecological criteria are described. For the computation, the implemented algorithms use data including the vegetation indexes, Digital Terrain Model (DTM), Digital Surface Model (DSM) and a 3D point cloud classification. All the raw data are collected by UAVs (Unmanned Aircraft Vehicle) equipped with a 3D Lidar, multispectral camera and RGB camera. Interpreting all the raw data collected by these sensors, using a multi-attribute approach, the WEQUI index is assessed. The computed ecological index is then used to assess the riparian environmental quality at ex-ante and ex-post river stabilization works. This index, integrated with additional not-technical or not-ecological indicators such as investment required, maintenance costs or social acceptance, can be used in multicriteria analyses in order to evaluate the intervention from a wider point of view. The platform is expected to be attractive for GI designers and policy makers by providing a shared environment, which is able to integrate the method of detection and evaluation of complex indexes and a multidimensional evaluation supported by an expert guide.

ENAC, the Italian Civil Aviation Authority, has published the regulation for remotely piloted aircraft systems (RPAS) with a maximum take-off mass of less than 150 kg. The aim of this paper is the application of Italian regulatory prescriptions for risk assessment to a family of RPAS. The results of this analysis, performed in collaboration with ENAC, are compared with other available methods, providing a comprehensive insight for mission feasibility and operational implications in a set of realistic application cases. Practical solutions are proposed for risk mitigation of RPAS specialized operations.