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Wind Defiant Morphing Drones

Victor Casas Rochel, Dario Floreano, William John Stewart, Charalampos Vourtsis

Intense winds are a challenge for vertical take-off and landing drones with wings. In particular, in the hovering regime, wings are sensitive to wind currents that can be detrimental to their operational and energetic performances. Tail-sitters are particularly prone to those wind currents because their wings are perpendicular to the incoming wind during hovering. This wind generates a large amount of drag and can displace and destabilize the vehicle, possibly leading to catastrophic failures. Herein, our morphing strategy demonstrates in a custom-built 1.8 kg tail-sitter with morphing wings that can actively resist winds and leverage them to increase its aerodynamic efficiency. It is shown that adaptive wing morphing during hovering in adverse wind conditions can reduce normalized energy consumption up to 85%, increase attitude and positional stability, and leverage wind energy to increase its yaw angular rate up to 200% while decreasing motor saturation levels.

2023

A Lightweight Device for Energy Harvesting from Power Lines with a Fixed-Wing UAV

Dario Floreano, William John Stewart

Modern UAVs (Unmanned Aerial Vehicles) suffer from restrictions in flight range and time due to battery capacity limitations. One way to overcome these limitations is to harvest energy from overhead power lines. A growing body of scientific literature has documented the development of energy harvesters on multirotor UAVs. However, to date, there have been no implementations on a fixed-wing UAV. In this paper we build upon a previously developed passive perching mechanism for fixed-wing UAVs by incorporating into it a split-core transformer for energy harvesting. We validate the perching mechanism as well as battery recharging in a realistic outdoor environment. We find that a minimum speed of 1.25m/s is required to successfully perch on the power line. This is below the stall speed of the UAV used in this project. Furthermore, experiments verified that no damage was done to the power line during perching, as the induced forces were equivalent to 1m/s wind gusts. Characterization of the energy harvesting shows that with a maximum of 3.3W of power from the harvester, we can fully charge a 2200mAh battery in 2.2 hours. Weighing only 420g, our device is the lightest energy harvester developed to date.

IEEE2022

How to compete with robots by assessing job automation risks and resilient alternatives

Dario Floreano, Rafael Lalive, Nicola Nosengo, Antonio Paolillo, Fabrizio Schiano, William John Stewart, Davide Zambrano

The effects of robotics and artificial intelligence (AI) on the job market are matters of great social concern. Economists and technology experts are debating at what rate, and to what extent, technology could be used to replace humans in occupations, and what actions could mitigate the unemployment that would result. To this end, it is important to predict which jobs could be automated in the future and what workers could do to move to occupations at lower risk of automation. Here, we calculate the automation risk of almost 1000 existing occupations by quantitatively assessing to what extent robotics and AI abilities can replace human abilities required for those jobs. Furthermore, we introduce a method to find, for any occupation, alternatives that maximize the reduction in automation risk while minimizing the retraining effort. We apply the method to the U.S. workforce composition and show that it could substantially reduce the workers’ automation risk, while the associated retraining effort would be moderate. Governments could use the proposed method to evaluate the unemployment risk of their populations and to adjust educational policies. Robotics companies could use it as a tool to better understand market needs, and members of the public could use it to identify the easiest route to reposition themselves on the job market.

2022