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Project #4: Experimental Testing of Allocation of Multiple UAVs

Project #4: Experimental Testing of Allocation of Multiple UAVs. Tim Arnett, Aerospace Engineering, Junior, University of Cincinnati Devon Riddle, Aerospace Engineering, Junior University of Cincinnati ASSISTED BY: Chelsea Sabo, Graduate Research Assistant Dr. Kelly Cohen, Faculty Mentor.

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Project #4: Experimental Testing of Allocation of Multiple UAVs

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  1. Project #4: Experimental Testing of Allocation of Multiple UAVs Tim Arnett, Aerospace Engineering, Junior, University of Cincinnati Devon Riddle, Aerospace Engineering, Junior University of Cincinnati ASSISTED BY: Chelsea Sabo, Graduate Research Assistant Dr. Kelly Cohen, Faculty Mentor

  2. Search and Rescue Weather Observation Forest Fire Monitoring Motivation & Operational Goals of Experimental Testing • Traffic Surveillance • Border Patrol • Military

  3. Learn to interface with hardware for controller development Understand the benefits and disadvantages of using different routing algorithms for UAVs Project Goals

  4. Objective 1: Interface with cooperative control development hardware • Interface and run algorithms on AR Drones • Interface and run algorithms on AMASE • Objective 2: Validate task allocation algorithm both in simulation and experimentally • Objective 3: Test and compare cooperative control strategies for UAVs Objectives

  5. AR Drone • OptiTrack System • Software Interface • Waypoint Following Algorithm • PID Control • Fuzzy Logic Control • Potential-based Control Experimental Setup

  6. AR Drone • Commercially available quadrotor • Can be controlled by a device using wireless network adapter Experimental Setup

  7. Optitrack System • Cameras provide real time position data • Data can be imported into MatLab Experimental Setup

  8. Software Interface • PC client with wireless capability • Wireless router to connect to multiple drones Experimental Setup

  9. Waypoint Following Algorithm • PID Control • Fuzzy Logic Control • Potential-based Control Experimental Setup

  10. Communication Pathway

  11. AR Drone requires commands in text strings with values formatted as a 32-bit signed integer • Command string example • CMD = sprintf('AT*PCMD=%d,%d,%d,%d,%d,%d\r',i,1,0,1036831949,0,0); • fprintf(ARc, CMD) • Arguments in order are sequence, flag, roll, pitch, ascent rate, and yaw rate Command Value Conversion

  12. AMASE

  13. A simulation program. • Sets up scenarios • Runs the main simulation that is wanted • Has the capabilities of analyzing the results as the simulation is run. Basic Overview

  14. The Map • Direct XML-editing (extensible markup language) • The Event Editor • The features mentioned above are the three basic methods use for entering information into a scenario to simulate it. • Multi Flight • CMASI Important Features

  15. Common Mission Automation Services Interface • A system of interactive objects that pertain to the command and control of a UAV system. • Communicate with the components • LMCP • Defines data types and enumerations. CMASI

  16. Timeline

  17. Challenges • Modeling the system for controller • Communicating with drone(s) Conclusions

  18. Questions?

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