Nonlinear Geometric and Differential Geometric Guidance of UAVs with Vision Sensing for Reactive Collision Avoidance

Abstract

This paper describes the integration of Nonlinear Geometric Guidance and Differential Geometric Guidance with vision sensing for UAV reactive obstacle avoidance as well as waypoint tracking. A 2D passive vision sensor has been applied to sense the surrounding environment in order to detect obstacles and locate destination. An Extended Kalman Filter is developed to estimate the obstacle and target position based on noisy measurements from vision sensor and known system dynamics. The Collision Cone approach is applied in order to detect any incoming collision and calculate an alternate aiming point to avoid it. Once the aiming point is known, one of the two nonlinear guidance laws, Nonlinear Geometric Guidance and Differential Geometric Guidance, have been applied for guidance purpose. The algorithm developed has been validated from a number of simulation studies in threedimensional
scenario.