An energy efficient IoD static and dynamic collision avoidance approach based on gradient optimization

Abstract

Internet of Drones (IoD) formation offers a wide variety of applications in military and civilian environments. In highly congested terrain, dynamic and static obstacles have a critical impact on IoD performance. One of the critical challenges in IoD missions is avoiding obstacles for successfully and safely completing their tasks. The limited flight time of a drone is another challenge. Thus, IoD has to be provided by an intelligent and accurate energy-efficient collision avoidance algorithm in which IoD paths are modified online to guarantee drones safety. This paper presents an energy-efficient strategy to avoid static and dynamic collisions with minimum energy required for drones to reach their destinations safely. We develop a novel algorithm to avoid multiple static and dynamic obstacles of different sizes within a limited detection range with energy consumption minimization. To do so, the gradient-based approach is utilized in the proposed algorithm for fast and quick convergence. Furthermore, the proposed algorithm allows drones to be in hovering or backtracking states; or they can fly vertically in other cases. More importantly, the results validate the efficiency and accuracy of the proposed algorithm in a dense environment that involves high collision risk with obstacle relative speed up to 10 meters/sec.