No abstract

No abstract

This paper presents a strategy for end-body positioning maneuvers using a towed cablebody system where a fixed wing Unmanned Aerial Vehicle (UAV) is stabilized in a circular orbit. High precision maneuvers such as object pickup/dropoff are typically performed by rotorcraft UAVs, but a successful fixed-wing concept would greatly increase the possible range for this type of operation and enable missions into more remote locations. Circularly towed cable-body systems have been shown capable, both analytically and experimentally, of maintaining stable configurations with the towed endbody maintaining a small motion respective to a point on the ground. However, no known efforts consider small to medium scale UAV operations for object pickup/dropoff/manipulation. A viable concept must be able to perform well when subjected to likely disturbances such as wind that causes the center of orbit for the towed endbody to be offset downwind of the UAV orbit. It is a primary goal of this paper to develop robust UAV path control that is able to stabilize the towed endmass in the presence of both moderate disturbances and modelling uncertainties. An optimized disturbance-free planned path that considers the UAV performance constraints is computed offline for the desired UAV towed system. A nonlinear sliding mode controller is developed to provide robust path control. To compensate for persistent winds or disturbances, the optimized disturbance-free orbit is inclined vertically to achieve an even tug on the towcable (i.e stabilize the measured cable tension force).

No abstract

Emerging precision agriculture techniques rely on the frequent collection of high-quality data which can be acquired efficiently by unmanned aerial systems (UAS). The main obstacle for wider adoption of this technology is related to UAS operational costs. The path forward requires a high degree of autonomy and integration of the UAS and other cyber physical systems on the farm into a common Farm Management System (FMS) to facilitate the use of big data and artificial intelligence (AI) techniques for decision support. Such a solution has been implemented in the EU project AFarCloud (Aggregated Farming in the Cloud). The regulation of UAS operations is another important factor that impacts the adoption rate of agricultural UAS. An analysis of the new European UAS regulations relevant for autonomous operation is included. Autonomous UAS operation through the AFarCloud FMS solution has been demonstrated at several test farms in multiple European countries. Novel applications have been developed, such as the retrieval of data from remote field sensors using UAS and in situ measurements using dedicated UAS payloads designed for physical contact with the environment. The main findings include that (1) autonomous UAS operation in the agricultural sector is feasible once the regulations allow this; (2) the UAS should be integrated with the FMS and include autonomous data processing and charging functionality to offer a practical solution; and (3) several applications beyond just asset monitoring are relevant for the UAS and will help to justify the cost of this equipment.