  Energy efficiency is of critical importance to trajectory planning for UAV
swarms in obstacle avoidance. In this paper, we present $E^2Coop$, a new scheme
designed to avoid collisions for UAV swarms by tightly coupling Artificial
Potential Field (APF) with Particle Swarm Planning (PSO) based trajectory
planning. In $E^2Coop$, swarm members perform trajectory planning cooperatively
to avoid collisions in an energy-efficient manner. $E^2Coop$ exploits the
advantages of the active contour model in image processing for trajectory
planning. Each swarm member plans its trajectories on the contours of the
environment field to save energy and avoid collisions to obstacles. Swarm
members that fall within the safeguard distance of each other plan their
trajectories on different contours to avoid collisions with each other.
Simulation results demonstrate that $E^2Coop$ can save energy up to 51\%
compared with two state-of-the-art schemes.
