Drone Hitching a Ride

New Drone Can Hitch a Ride on a Moving Car Hitchhiker latches on using trajectory tracking and suction cups    MICHELLE HAMPSON  

A box with a picture of a small teal car in front of a white backdrop, and a drone attached to the box's back

The new Hitchhiker drone developed by researchers at Shanghai Jiao Tong University can land on vertical moving surfaces. SENSEN LIU

JOURNAL WATCH DRONE SURVEYING

This article is part of our exclusive IEEE Journal Watch series in partnership with IEEE Xplore.

Drones are being used for everything, it seems: surveillance, delivery tasks, search and rescue efforts. But as these handy fliers take on more unique and difficult tasks, they need to be able to land in increasingly challenging scenarios. Now, a newly designed drone called Hitchhiker is able to land not just on inclined surfaces, but inclined surfaces in motion—like the side of a moving car.

Sensen Liu designed Hitchhiker as part of his postdoctoral work at the Lab of Cooperative Intelligence of Unmanned Systems at Shanghai Jiao Tong University’s School of Mechanical Engineering. “Our interest stems from the fact that many structures—including buildings, bridges, and ground vehicles—feature inclined surfaces that are difficult for traditional drones to land on,” he explains. “By creating drones with this capability, we can leverage these surfaces as landing sites and expand the possibilities for the use of drone technology.”

Liu’s team is particularly interested in developing drones that can land on the side of moving cars. “The drone would be capable of scouting the surrounding environment while the automobile is in motion, allowing for real-time analysis of the environment,” explains Liu.

Once the drone is done scouting, it could latch onto the side of the car in order to help conserve energy, delaying the time needed before its batteries must be swapped or recharged.

To create such a drone, Liu and colleagues, under the supervision of Wei Dong, an associate professor at Shanghai Jiao Tong University, developed a trajectory planning algorithm that accounts for the individual thrust of each rotor of the quadcopter. It utilizes a two-stage tracking approach that analyzes both the drone’s position and attitude.  ... '