MSCS Thesis Presentation - Hunter Rhoades
April 30, 2026 12:00PM—1:30PM
Location:
In Person
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Traffic21 Classroom, Gates Hillman 6501
Speaker:
HUNTER RHOADES,
Master's Student, Computer Science Department, Carnegie Mellon University
Computer vision-enabled autonomous drone flight creates challenges with reproducibility and behavior assessment due to inherent variability in the models that provide cognitive function to the vehicle. These challenges are most visible when attempting to validate control logic in the automation pipeline and when benchmarking for the purpose of making objective assessments on agility and maneuverability. In this work we begin by exploring the current state of simulation technology and its particular applications in the development and fielding of autonomous drone systems, exposing a sudden jump from simulation-heavy prototyping to end-to-end full system testing involving physical flight that increases the difficulty of validating correctness and incurs unnecessary risk. We present the concept of a SensorTwin, a novel application of simulation technology that seeks to reduce the identified gap between early phase software and hardware-in-the-loop style simulation and late phase digital twin style simulation by isolating the visual feed and cognitive engine components of a physical vehicle-automation pipeline system. We provide a concrete implementation of a SensorTwin built over the SteelEagle Autonomous Drone system and demonstrate proof of concept by evaluating the performance of the SensorTwin-augmented system on existing cognitive task evaluations. We also introduce a novel set of agility evaluation tests, referred to as the Autonomous Agility Benchmark, with the intent of enabling future relative comparison across vehicle platforms, autonomy pipelines, and cognitive function implementations. An initial dataset for the benchmark suite is produced through physical flight augmented by the SensorTwin implementation and analyzed to provide initial objective and subjective insights on agility assessment specific to the automated drone setting.
Thesis Committee
Mahadev Satyanarayanan (Chair)
Babu Pillai
Mihir Bala
Additional Information
For More Information:
amalloy@cs.cmu.edu