Mory Gharib and Ioannis Mandralis with the ATMO robot. (Image: Lance Hayashida/Caltech)

Specialized robots that can both fly and drive typically touch down on land before attempting to transform and drive away. But when the landing terrain is rough, these robots sometimes get stuck and are unable to continue operating. Now, a team of Caltech engineers has developed a real-life Transformer that has the "brains" to morph in mid-air, allowing the drone-like robot to smoothly roll away and begin its ground operations without pause. The increased agility and robustness of such robots could be particularly useful for commercial delivery systems and robotic explorers.

The new robot, dubbed ATMO (aerially transforming morphobot), uses four thrusters to fly, but the shrouds that protect them become the system's wheels in an alternative 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 the sophisticated control system that drives it 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," said Lead Author Ioannis Mandralis (MS '22), graduate student in aerospace at Caltech. For example, he said, birds fly and then change their body morphology to slow themselves down and avoid obstacles. "Having the ability to transform in the air unlocks a lot of possibilities for improved autonomy and robustness," Mandralis said.

But mid-air transformation also poses challenges. Complex aerodynamic forces come into play both because the robot is close to the ground and because it is changing its shape as it morphs.

"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," said Mory Gharib (PhD '83), Hans W. Liepmann Professor of Aeronautics and Medical Engineering, Director and Booth-Kresa Leadership Chair of Caltech's Center for Autonomous Systems and Technologies (CAST), and Director of the Graduate Aerospace Laboratories of the California Institute of Technology (GALCIT). 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. When that air hits the ground, some portion of it bounces back up; if the helicopter comes in too quickly, it can get sucked into a vortex formed by that reflected air, causing the vehicle to lose its lift.

In ATMO's case, the level of difficulty is even greater. Not only does the robot have to contend with complex near-ground forces, but it also has four jets that are constantly altering the extent to which they are shooting toward each other, creating additional turbulence and instability.

To better understand these complex aerodynamic forces, the researchers ran tests in CAST's drone lab. They used what are called load cell experiments to see how changing the robot's configuration as it came in for landing affected its thrust force. They also conducted smoke visualization experiments to reveal the underlying phenomena that lead to such changes in the dynamics.

The researchers then fed those insights into the algorithm behind a new control system they created for ATMO. The system uses an advanced control method called model predictive control, which works by continuously predicting how the system will behave in the near future and adjusting its actions to stay on course.

Here is an exclusive Tech Briefs interview, edited for length and clarity, with Mandralis.

Tech Briefs: What was the biggest technical challenge you faced while developing ATMO?

(Image: Ioannis Mandralis/Communications Engineering)

Mandralis: The biggest technical challenge we faced was developing a control system capable of autonomously performing the air-to-ground transition maneuver. Mid-air transformation significantly changes the dynamics of the robotic system — requiring an algorithm that can adapt and react to these changing conditions while dealing with unexpected disturbances like gusts of wind, or the interaction between the air and the ground.

Tech Briefs: Can you explain in simple terms how it works please?

Mandralis: The control algorithm works using a technique called Model Predictive Control. In this method the onboard computer uses a physics-based model of the robotic system and its interaction with the world to predict what will happen for a given time in the future. Using this information, and information about the task it is trying to accomplish e.g. landing on wheels, it can compute the actions it should take to achieve its goal.

Tech Briefs: What was the catalyst for ATMO?

Mandralis: Our team at Caltech is generally interested in robotic systems that are able to explore the world using a combination of different modes of locomotion, with a specific emphasis on combining flying capabilities with terrestrial capabilities such as driving. Creating a robotic system that could combine these two modes using mid-air transformation was the natural next step.

Tech Briefs: Do you have any set plans for further research/work/etc.? If not, what are your next steps?

Mandralis: We are currently working on endowing robotic systems like ATMO with the onboard perception necessary to achieve fully autonomous operation. We are interested in using onboard cameras to take effective decisions about where and when to land, transform, fly, or drive, as well as to avoid obstacles and ensure safety when operating around humans or in cluttered urban environments.

Tech Briefs: Do you have any advice for researchers aiming to bring their ideas to fruition (broadly speaking)?

Mandralis: The approach that has been the most useful for me has always been to simplify a problem down to the bare essentials before trying to solve it. When faced with long term projects, the complexity can often be overwhelming — breaking problems down into simpler tasks will significantly catalyze progress. It is also very important to have a great team to work with! This will make the research process much more enjoyable and result in new ideas as well as fresh perspectives.

Topics:
Automation Design Physical Sciences Robotics Unmanned Air Vehicles/Systems (UAV/UAS)

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    Transcript

    00:00:04 Meet Atmo, the aerially transforming morphabot that can smoothly transition between ground and air through midair transformation. Atmo is capable of driving, engaging its thrusters to fly and land seamlessly on its wheels. This is achieved using a unified structural and actuation system that transforms the robot from quadrotor to ground mode using only one motor. We also study the

    00:00:28 aerodynamics of midair transformation using smoke visualization and load cell testing. Obtaining new insights in the aerodynamics of aerial transformation. This enables us to push the limits of the maneuvers that can be achieved. We exploited the studied aerodynamics using a model predictive controller with an adaptive objective function. Our method is applicable for

    00:00:50 emergency slope landings as well as quick transitions from air to ground by landing or taking off with forward velocity. Our method may also increase the fall tolerance of robots deployed on the field. When transforming on the ground, rough terrain may trap the robot. Instead, landing in ground configuration can avoid these situations, increasing robustness.

    00:01:13 This work is one example of how mid-air transformation can increase the agility and robustness of robotic explorers.