Join us on the UC Davis campus to hear Dr. Mark Mueller discuss new solutions for two common challenges faced in drone flight.

Hardware / Controls Co-design to Overcome Challenges for Aerial Robots

Featuring Mark Mueller, Ph.D., Associate Professor of Mechanical Engineering, Principal Investigator, High Performance Robotics Laboratory (HiPeRLab), University of California, Berkeley

WHAT: Free one-hour event with a talk by Dr. Mark Mueller

WHEN: Tuesday, March 11, 2025, 12:30–1:30 PM

WHERE: Physical and Data Sciences Building (formerly PSEL) on the UC Davis campus

REMOTE: via Zoom

WHO SHOULD ATTEND: This event is open to all, whether you are a part of the university community or the public.

Join the AI Institute for Next Generation Food Systems (AIFS) on the UC Davis campus for an event demonstrating how developments in hardware and controls co-design are helping to break through persistent challenges in aerial robotics.

Unmanned Aerial Vehicles (UAVs), or drones, have become ubiquitous, but, like most robots, they still struggle to operate at high speeds in unstructured, cramped environments. Learn about two exemplary challenges for aerial robots and potential solutions:

1. Flight through narrow, unstructured environments, and
2. Long duration and range flight within the constraints of battery-electric power.

AIFS Faculty, Dr. Mark Mueller, will present some of his group's work on enhancing aerial robots, including purely algorithmic approaches ("how can I do more with the hardware I already have?") and with hardware co-design ("how can I change the vehicle so that the hard problem is actually easy?").

By considering a vehicle's mechanical design simultaneously with the design of controls and automation algorithms, we have more degrees of freedom to find creative solutions to problems.

Finally, Dr. Mueller will discuss some work on adaptive and learning control, specifically for robustness to parametric uncertainty.

For flight through narrow environments, Dr. Mueller will present an algorithmic approach for high speed path planning that incorporates perception uncertainty, and can be used on a standard drone. He will then present two alternative approaches that modify the system design: one a vehicle that can change its shape to fit through narrower spaces, and a second that is highly collision resilient, and for whom collisions are therefore neither mission- nor safety-critical.

For overcoming energetic challenges, Dr. Mueller will present a strategy for real-time optimization of flight characteristics for a vehicle, specifically using extremum seeking control to modify the system airspeed and yaw angle; an algorithm that can be applied to any aerial robot. We then again show two design modifications to work around the problem – first, a morphing system that can reduce its drag area at speed, and secondly a system capable of mid-air battery replacement for indefinite flight.

This event is being offered in a hybrid format to attend in person or online.

Lunch will be provided for in-person attendees.