  This work focuses on low-energy collision avoidance and formation maintenance
in autonomous swarms of drones. Here, the two main problems are: 1) how to
avoid collisions by temporarily breaking the formation, i.e., collision
avoidance reformation, and 2) how do such reformation while minimizing the
deviation resulting in minimization of the overall time and energy consumption
of the drones. To address the first question, we use cellular automata based
technique to find an efficient formation that avoids the obstacle while
minimizing the time and energy. Concerning the second question, a near-optimal
reformation of the swarm after successful collision avoidance is achieved by
applying a temperature function reduction technique, originally used in the
point set registration process. The goal of the reformation process is to
remove the disturbance while minimizing the overall time it takes for the swarm
to reach the destination and consequently reducing the energy consumption
required by this operation. To measure the degree of formation disturbance due
to collision avoidance, deviation of the centroid of the swarm formation is
used, inspired by the concept of the center of mass in classical mechanics.
Experimental results show the efficiency of the proposed technique, in terms of
performance and energy.
