AOSoar: Autonomous Orographic Soaring of a Micro Air Vehicle

TL;DR

This paper introduces a fully autonomous method for micro air vehicles to perform orographic soaring by combining an advanced control system with an optimization technique, significantly reducing energy use and adapting to changing wind conditions.

Contribution

It presents a novel autonomous soaring approach using INDI control and simulated-annealing optimization, enabling MAVs to find and utilize soaring spots without prior wind knowledge.

Findings

Autonomous soaring achieved for up to 30 minutes in wind tunnel tests.

Throttle usage was reduced to 0.25% during soaring, compared to 38% in powered flight.

MAV successfully adapts to changing wind conditions by finding new soaring spots.

Abstract

Utilizing wind hovering techniques of soaring birds can save energy expenditure and improve the flight endurance of micro air vehicles (MAVs). Here, we present a novel method for fully autonomous orographic soaring without a priori knowledge of the wind field. Specifically, we devise an Incremental Nonlinear Dynamic Inversion (INDI) controller with control allocation, adapting it for autonomous soaring. This allows for both soaring and the use of the throttle if necessary, without changing any gain or parameter during the flight. Furthermore, we propose a simulated-annealing-based optimization method to search for soaring positions. This enables for the first time an MAV to autonomously find a feasible soaring position while minimizing throttle usage and other control efforts. Autonomous orographic soaring was performed in the wind tunnel. The wind speed and incline of a ramp were changed during the soaring flight. The MAV was able to perform autonomous orographic soaring for flight times of up to 30 minutes. The mean throttle usage was only 0.25% for the entire soaring flight, whereas normal powered flight requires 38%. Also, it was shown that the MAV can find a new soaring spot when the wind field changes during the flight.