Watch: Drone Swarm Avoiding Obstacles in Thick Forest

Watch: Drone Swarm Avoiding Obstacles in Thick Forest

Photo illus. forest by Pixabay

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Drone swarms have been usually tested in open environments without obstacles, or with the location of those obstacles pre-programmed. Highly cluttered environments such as dense forests remain inaccessible to drones and even more so to swarms of drones. Previously unknown surroundings and narrow corridors combined with requirements of swarm coordination are challenging. 

In a recent experiment, led by scientists at Zhejiang University in China, a swarm of 10 bright blue drones lifts off in a bamboo forest, then swerves its way between cluttered branches, bushes and over uneven ground as it autonomously navigates the best flight path through the woods.

The researchers built miniature but fully autonomous drones with a trajectory planner that can function in a timely and accurate manner based on limited information from onboard sensors. 

The palm-sized robots were purpose-built, with depth cameras, altitude sensors and an on-board computer. The biggest advance was a clever algorithm that incorporates collision avoidance, flight efficiency and coordination within the swarm.

Since these drones do not rely on any outside infrastructure, such as GPS, swarms could be used in a wide variety of applications, including aerial mapping for conservation and disaster relief work. For example, they could be sent into earthquake-hit areas to survey damage and identify where to send help, or into buildings where it’s unsafe to send people. Another possible use is having the swarm collectively lift and deliver heavy objects. However, it will take time until the technology matures. 

The Chinese team tested their drones in different scenarios – swarming through the bamboo forest, avoiding other drones in a high-traffic experiment, and having the robots follow a person’s lead, according to channelnewsasia.com and international news agencies.

The research paper was published in the journal Science Robotics.