Science Daily October 23, 2019
An international team of researchers (the Netherlands, UK) developed the swarm gradient bug algorithm (SGBA) that allows a swarm of tiny flying robots to autonomously explore an unknown environment and subsequently come back to the departure point. It maximizes coverage by having robots travel in different directions away from the departure point. The robots navigate the environment and deal with static obstacles on the fly by means of visual odometry and wall-following behaviors. They communicate with each other to avoid collisions and maximize search efficiency. The robots perform a gradient search toward a home beacon to come back to the departure point. They demonstrated that SGBA allows a group of 33-g commercial off-the-shelf quadrotors to successfully explore a real-world environment. In a proof-of-concept search-and-rescue mission the robots captured images to find “victims” in an office environment. The developed algorithms generalize to other robot types and lay the basis for tackling other similarly complex missions with robot swarms in the future…read more. Open Access TECHNICAL ARTICLE
Hardware specifications and comparison. Credit: Science Robotics 23 Oct 2019: Vol. 4, Issue 35, eaaw9710