Abstract
This work presents a decentralized mobility control algorithm for an optimal end-to-end communication chain using a team of unmanned aircraft acting solely as communication relays. The chaining controller drives the location of a virtual control point, using estimates of the communication objective function gradient calculated using stochastic approximation techniques, to locations of improved relaying for unmanned aircraft. The gradient estimate is derived from observation data of the communication objective function taken along a path generated by the aircraft orbiting about the control point. Flight experiments show that an unmanned aircraft can measure the signal-to-noise-and-interference ratio fields from IEEE 802.11b/g (WiFi) communication links; generate estimates of the field gradients using the least-squares gradient estimation method; and use the gradient estimates to drive a control point to a location that improves communication capacity.
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