Adaptive Control Strategy for Constant Optical Flow Divergence Landing
This addresses the challenge of safe autonomous landing for MAVs, though it is incremental as it builds on existing bio-inspired methods.
The paper tackled the problem of instability in optical flow-based landing for Micro Air Vehicles due to noise and delay in flow divergence estimates, proposing an adaptive control strategy that adjusts gains based on height detection and trajectory deviations, resulting in stable landings demonstrated in real-world indoor and windy outdoor environments.
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.