Researchers at the California Institute of Technology (Caltech) have created a real-life transformer robot that's changing how machines navigate between air and ground. The Aerially Transforming Morphobot (ATMO) can seamlessly shift from flying drone to rolling vehicle without interruption, using a single motor to control its transformation.
Unlike conventional hybrid robots that must land before reconfiguring, ATMO has the intelligence to morph in midair, allowing it to smoothly roll away and begin ground operations without pause. The increased agility and robustness could be particularly useful for commercial delivery systems and robotic explorers. The robot uses four thrusters to fly, but the shrouds that protect them become the system's wheels in its driving configuration. The whole transformation relies on a single motor to move a central joint that lifts ATMO's thrusters up into drone mode or down into drive mode.
The researchers describe the robot and its sophisticated control system in a paper recently published in the journal Communications Engineering. "We designed and built a new robotic system that is inspired by nature—by the way that animals can use their bodies in different ways to achieve different types of locomotion," says Ioannis Mandralis, a graduate student in aerospace at Caltech and lead author of the paper. For example, birds fly and then change their body morphology to slow themselves down and avoid obstacles.
The engineering challenge was significant. "Even though it seems simple when you watch a bird land and then run, in reality this is a problem that the aerospace industry has been struggling to deal with for probably more than 50 years," says Mory Gharib, the Hans W. Liepmann Professor of Aeronautics and Medical Engineering and director of Caltech's Center for Autonomous Systems and Technologies (CAST). All flying vehicles experience complicated forces close to the ground. Think of a helicopter, as an example. As it comes in for a landing, its thrusters push lots of air downward.
To tackle these complex aerodynamic challenges, the team conducted extensive experiments in Caltech's drone lab, including load cell tests and smoke visualizations to understand how airflow changes during morphing. These insights were used to design a smart control system based on model predictive control, which allows the robot to predict how its motion will change and make real-time adjustments to maintain stability. The team hopes ATMO's unique blend of agility, resilience, and intelligence will pave the way for the next generation of autonomous machines, especially in fields like delivery, search and rescue, and planetary exploration, where adapting to unpredictable environments is key.