Bucknell University · Research with Professor Craig Beal
Autonomous RC Vehicle
This research used a scaled RC-car platform to investigate autonomous steering. Overhead-camera tracking, Arduino actuation, and steering algorithms were brought together in a physical test environment.
- Project context
- Controls research under Professor Craig Beal at Bucknell University.
- Engineering challenge
- Connect measured position and orientation to physical steering behavior.
- Outcome
- Working autonomous tracking and steering with a demonstrated higher-speed operating baseline
01 / Development
Building a measurable test platform
A ceiling-mounted webcam viewed a white test surface. Red and blue markers on the car supported color filtering and circle identification, allowing its position and orientation to be tracked at up to 30 frames per second. An Arduino interface controlled speed and steering through the RC controller.
01 / Observe
Overhead camera
Capture the vehicle and its red and blue tracking markers.
02 / Estimate
Position & orientation
Identify the markers and calculate the vehicle’s relationship to the track.
03 / Actuate
Speed & steering
Send commands through the Arduino interface to the RC controller.
02 / Development
Closing the steering loop
The initial controller used distance and heading error relative to a circular track. Physical tests connected the steering calculations to the car’s actual motion.
What the controller corrects
- Lateral error
- How far the vehicle is from the target path
- Heading error
- How its orientation differs from the direction of the path
The steering command combines these errors so the vehicle can return toward the path while aligning with its direction.
03 / Development
Expanding the virtual track
The method was extended to calculate the track’s tangent angle at each point. Feed-forward steering anticipated each turn, while feedback corrected the vehicle’s orientation and distance from the track. Physical tests connected the algorithms to the car’s actual motion.
04 / Development
Testing at higher speed
The projected-point controller established a higher-speed baseline for evaluating autonomous path following. Steering from a point ahead of the vehicle connected the correction to the direction the car was traveling.
At that operating point and a 30-frame-per-second update rate, the vehicle travels approximately 38 mm between camera observations. That gap makes observation timing part of the control problem: steering uses discrete measurements of a continuously moving vehicle. Predicting position between frames was identified as a direction for further research.