Adaptive Control Strategy for Constant Optical Flow Divergence Landing

TL;DR

This paper presents an adaptive control strategy for MAV landings that mimics insect behavior, using flow divergence and control gain adjustments to ensure stable descent despite noise and delays.

Contribution

It introduces a novel adaptive control method that uses flow divergence and instability theory to enable safe, stable autonomous landings in variable conditions.

Findings

Successful indoor and outdoor experiments demonstrating stability

Adaptive gains improve landing robustness against noise and delays

Utilization of flow divergence for distance estimation during landing

Abstract

Bio-inspired methods can provide efficient solutions to perform autonomous landing for Micro Air Vehicles (MAVs). Flying insects such as honeybees perform vertical landings by keeping flow divergence constant. This leads to an exponential decay of both height and vertical velocity, and allows for smooth and safe landings. However, the presence of noise and delay in obtaining flow divergence estimates will cause instability of the landing when the control gains are not adapted to the height. In this paper, we propose a strategy that deals with this fundamental problem of optical flow control. The key to the strategy lies in the use of a recent theory that allows the MAV to see distance by means of its control instability. At the start of a landing, the MAV detects the height by means of an oscillating movement and sets the control gains accordingly. Then, during descent, the gains are reduced exponentially, with mechanisms in place to reduce or increase the gains if the actual trajectory deviates too much from an ideal constant divergence landing. Real-world experiments demonstrate stable landings of the MAV in both indoor and windy outdoor environments.