Fast collective evasion in self-localized swarms of unmanned aerial vehicles

Abstract

A novel approach for achieving fast evasion in self-localized swarms of unmanned aerial vehicles (UAVs) threatened by an intruding moving object is presented in this paper. Motivated by natural self-organizing systems, the presented approach of fast and collective evasion enables the UAV swarm to avoid dynamic objects (interferers) that are actively approaching the group. The main objective of the proposed technique is the fast and safe escape of the swarm from an interferer discovered in proximity. This method is inspired by the collective behavior of groups of certain animals, such as schools of fish or flocks of birds. These animals use the limited information of their sensing organs and decentralized control to achieve reliable and effective group motion. The system presented in this paper is intended to execute the safe coordination of UAV swarms with a large number of agents. Similar to natural swarms, this system propagates a fast shock of information about detected interferers throughout the group to achieve dynamic and collective evasion. The proposed system is fully decentralized using only onboard sensors to mutually localize swarm agents and interferers, similar to how animals accomplish this behavior. As a result, the communication structure between swarm agents is not overwhelmed by information about the state (position and velocity) of each individual and it is reliable to communication dropouts. The proposed system and theory were numerically evaluated and verified in real-world experiments.

MRS Drone: A Modular Platform for Real-World Deployment of Aerial Multi-Robot Systems

“…This is done by using ultraviolet LEDs that emit particular optical identification signals, which are detected and decoded using cameras equipped with an optical filter that significantly attenuates most of the image background [98,101], and thus simplifies the detection of the optical signals on the camera frame. This method has been tested with great success in multiple real-world deployments of swarms and formations of UAVs [2,27,39,58,66,102,103].…”

“…Nevertheless, bringing these swarm systems into the real world is a long-standing problem, due to the significant operative differences between laboratory environments and diverse, real-world environments. To deal with the demands of various real-world environments, the MRS platforms can be modified to handle the operating conditions required in plain fields, forests, dunes and deserts, hills, and much more [2,4,23,27,37,58,66,71]. One essential element of biologically-inspired swarming architectures is the perception-aware system, which allows for maintaining group cohesion and avoiding collisions between teammates.…”

“…28, where the swarm system demonstrated the ability to follow over uneven terrain. In [58], a bio-inspired evasion approach in a self-organized swarm of UAVs was introduced. Using the UVDAR system, MRS UAVs were able to avoid dynamic objects (predators) that were actively approaching the group.…”

MRS Modular UAV Hardware Platforms for Supporting Research in Real-World Outdoor and Indoor Environments

“…The compact group of robots was able to safely navigate through dense obstacle area using 2D LiDAR. In [27], a bioinspired evasion approach in self-organized swarm of UAVs was introduced. Using the UVDAR system, MRS UAVs were able to avoid dynamic objects (predators) that were actively approaching the group.…”

PACNav: a collective navigation approach for UAV swarms deprived of communication and external localization

“…The use of a group of UAVs can reduce mission time and provide the redundancy and safety that is critical in many real-world applications, such as mapping large areas [3], construction [4], agriculture [5], and search-and-rescue missions [6]. These applications have further motivated research on the collective motion of a group of UAVs [7][8][9]. Indeed, large groups of UAVs are effective in some scenarios where a single robot facing the problem may be unfeasible or difficult to solve.…”