An interval approach to multiple unmanned aerial vehicle collision avoidance

Abstract

Small/micro Unmanned Aerial Systems (UAVs) require the ability to operate with constraints of a diverse, automated airspace where obstacle telemetry is denied. This paper proposes a novel Sense, Detect and Avoid (SDA) algorithm with inherit resilience to sensor uncertainty. This is achieved through the interval geometric formulation of the avoidance problem, which by the use of interval analysis, can be extended to consider multiple obstacles. The approach is shown to demonstrate the ability to both tolerate sensor uncertainty and enact generated 3D avoidance trajectories. Monte-Carlo simulations demonstrate successful avoidance rates of 88%, 96% and 91% in two example collision scenarios and one multi-agent conflict scenario respectively.