Dealing with midair collisions in dense collective aerial systems

Abstract

The idea of creating collective aerial systems is appealing because several rather simple flying vehicles could join forces to cover a large area in little time in applications such as monitoring, mapping, search and rescue, or airborne communication relays. In most of these scenarios, a fleet of cooperating vehicles is dispatched to a confined airspace area and requested to fly close to a nominal altitude. Moreover, depending on the task each vehicle is assigned to, individual flight trajectories in this essentially two-dimensional space may interfere, resulting in disastrous collisions. This paper begins by introducing a probabilistic model to predict the rate of midair collisions that would occur if nothing is done to prevent them. In a second step, a control strategy for midair collision avoidance is proposed, which is interesting because it requires only local communication and information about flight altitudes. The proposed strategy is systematically analyzed in theory and simulation as well as in experiments with five physical aerial vehicles. A significant reduction in collision rates can be achieved. Statistically, values close to zero are possible when the swarm's density is below an applicationdependent threshold. Such low collision rates warrant an acceptable level of confidence in collision-free operation of a physical swarm. C 2011 Wiley Periodicals, Inc.

Underwater Robot Swarms: Challenges and Opportunities

“…Although many researchers have been pioneering this field over the past decade, very little demonstrations have been conducted with physical flying platforms. A few noticeable exceptions are Allred et al (2007); Beard et al (2006); Gancet et al (2005); Hauert et al (2010a); Hoffmann et al (2004); How et al (2004); Leven et al (2010); Melhuish and Welsby (2002). Two phases are shown here, in phase I, the robot group is directed to the West.…”

“…This issue however is seldom taken into account during trajectory planning. For this reason, researchers have been concentrating on having robots within collision range negotiate new trajectories in 2D or 3D space (Leven et al, 2010;Šišlák et al, 2007.…”

Aerial Collective Systems

“…Although many researchers have been pioneering this field over the past decade, very little demonstrations have been conducted with physical flying platforms. A few noticeable exceptions are Allred et al (2007); Beard et al (2006); Gancet et al (2005); Hauert et al (2010a);Hoffmann et al (2004); How et al (2004); Leven et al (2010); Melhuish and Welsby (2002). Two phases are shown here, in phase I, the robot group is directed to the West.…”

“…This issue however is seldom taken into account during trajectory planning. For this reason, researchers have been concentrating on having robots within collision range negotiate new trajectories in 2D or 3D space (Leven et al, 2010;Šišlák et al, 2007.…”

A Review on Collision Avoidance Systems for Unmanned Aerial Vehicles

“…Unlike the state projection that can be separately performed for each airplane, conflict metrics extraction necessitates the aggregation of the states of the different involved airplanes. The minimum separation distance, the time to the closest point of approach [14], the number of available avoidance manoeuvres, the conflict probability and the collision rate [15] are the most used conflict metrics in traditional conflict detection systems. Some new approaches use more complex and direct metrics than physical metrics.…”