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Sep 7, 2017 1:16 PM
| Last Modified: Oct 26, 2017 10:09 AM
John Salmon, PhD, Assistant Professor, Brigham Young University
Landon Wright, Research Assistant, Brigham Young University
This presentation was voted one of the three finalists for Best Contributed Paper.
Unmanned aerial vehicles (UAV) are becoming popular for both individuals and organizations to better accomplish various tasks and missions, including delivery of small payloads, building or equipment surveillance, and search and rescue operations. A UAV path planning simulator, using the JMP Scripting Language, enables rapid tuning of system parameters and exploration of UAV capabilities. The system uses proportional, derivative and integral control to determine how the aircraft should react in order to reach the desired state. This JMP UAV simulator is capable of planning a waypoint path through a simulated city dynamically created in a JSL 3D scene, based on user-defined inputs. The path planning algorithm applies Dubins car paths adapted for aircraft use. The predetermined path is presented alongside the simulation of the UAV, allowing for investigation and performance validation. All of the key tunable parameters of the simulator are presented as user editable values enabling real-time updating and tuning of the algorithms that govern the actions of the aircraft. The results and statistics of the Monte Carlo simulations are presented in the associated JMP dashboard to inform decision makers regarding the design and behavior of future UAV systems and path planning algorithms.