Omnidirectional visual odometry for flying robots using low-power hardware

Currently, flying robotic systems are in development for package delivery, aerial exploration in catastrophe areas, or maintenance tasks. While many flying robots are used in connection with powerful, stationary computing systems, the challenge in autonomous devices—especially in indoor-rescue or rural missions—lies in the need to do all processing internally on low power hardware. Furthermore, the device cannot rely on a well ordered or marked surrounding. These requirements make computer vision an important and challenging task for such systems. To cope with the cumulative problems of low frame rates in combination with high movement rates of the aerial device, a hyperbolic mirror is mounted on top of a quadrocopter, recording omnidirectional images, which can capture features during fast pose changes. The viability of this approach will be demonstrated by analysing several scenes. Here, we present a novel autonomous robot, which performs all computations online on low power embedde d hardware and is therefore a truly autonomous robot. Furthermore, we introduce several novel algorithms, which have a low computational complexity and therefore enable us to refrain from external resources.