This study used system control software and hardware to conduct control system design and path planning for Mission-based Swarm Main/sub Vehicles. The Raspberry 3 and PlayDuino controllers were used for system design and path planning, in order to control the formation transformation of the Mission-based Swarm Main/sub Vehicles based on each of the formation number. The system includes low-power micromotor, rubber tire, signal connector, Bluetooth receiver, wired/wireless router, Raspbrry 3, and PlayDuino controller, etc. Miniature automatic guided vehicle were used to simulate the prototype of the Mission-based Swarm Main/sub Vehicles. Python, a more accessible programming language than the C language, was used for writing the internal coding. Using the easy to write, low error rate, and readability characteristics of the Python language, it was used to find the optimal paths for the formation transformations. A miniature camera was setup above the Mission-based Swarm Main/sub Vehicles to identify the positions based on the color blocks on top of the vehicles. The signals were transmitted to the computer through Bluetooth receiver, which simulated satellite positioning conducted formation transformation of the vehicles within the limited area. The simulations demonstrated that within the limited area, using miniature camera to simulate satellite positioning, the vehicles were able to transform into five different formations successfully using optimal path planning.
|Effective start/end date||2017/08/01 → 2018/07/31|
- Main/sub Vehicle
- Raspberry 3
- Automatic Guided Vehicle
- Python language
- Formation Design
- Path Planning
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.