A robust real-time path planner for the collision-free navigation of multirotor aerial robots in dynamic environments
José Luis Sánchez-López, Jesús Pestana, Pascual Campoy · 2017
The development of deliberative capabilities is required to achieve an intelligent fully autonomous behavior of unmanned aerial systems. An important deliberative capability is the generation of collision-free paths in complex environments. This paper presents a robust real-time collision-free path planner used for the horizontal 2D navigation of multirotor aerial robots in dynamic environments. Its design, using geometric primitives to describe the environment combined with a launching time generation of a probabilistic roadmap graph, permits an efficient management of dynamic obstacles. The use of an A* discrete search algorithm, together with a potential field map as the cost function, allows to speed up the collision-free path computation ensuring that it never falls in local minima. Additionally, the velocity and acceleration along the collision-free planned path is calculated. The performance of the proposed path planner is evaluated in this paper with two simulations with complex environments including a labyrinth and dead ends, and with a real flight experiment where three fully autonomous aerial robots executed an emulated search and rescue mission. The proposed path planner has been released to the scientific community as an open-source software included in Aerostack2. In addition, it has extensively been used in multiple research projects with real flights, demonstrating its good performance.