Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2007. / Includes bibliographical references (p. 79-81).

Thesis (M.S.)--Rochester Institute of Technology, 2009. / Typescript. Includes bibliographical references (leaves 74-76).

Thesis (M.S. in Applied Mathematics)--Naval Postgraduate School, June 2010. / Thesis Advisor(s): Kang, Wei ; Second Reader: Zhou, Hong. "June 2010." Description based on title screen as viewed on July 14, 2010. Author(s) subject terms: Nonlinear model, trajectory optimization, state and control variables, cost function Includes bibliographical references (p. 59-60). Also available in print.

Thesis (M.S. in Electrical Engineering)--Naval Postgraduate School, June 2005. / Thesis Advisor(s): Phillip E. Pace Includes bibliographical references (p. 109). Also available online.

Thesis (MScIng)--University of Stellenbosch, 2005. / Bibliography. Also available via the Internet.

Thesis (M.S. in Joint Campaign Planning and Strategy)--Joint Forces Staff College, Joint Advanced Warfighting School, 2006. / "14 April 2006." Electronic version of original print document. Includes bibliographical references (p. 58-61).

Thesis (MScIng)--University of Stellenbosch, 2005. / Bibliography. Also available via the Internet.

Thesis (M.S.)--West Virginia University, 2006. / Title from document title page. Document formatted into pages; contains xi, 121 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 90-95).

This work presents a framework for the exploration and path planning for a collaborative UAV and UGV system. The system is composed of a UAV with a stereo system for obstacle detection and a UGV with no sensors for obstacle detection. Two exploration algorithms were developed to guide the exploration of the UAV. Both identify frontiers for exploration with the Dijkstra Frontier method using Dijkstra's Algorithm to identify a frontier with unknown space, and the other uses a bi-directional RRT to identify multiple frontiers for selection. The final algorithm developed was for to give the UGV partial plans when an entire plan is not yet found. This improves the overall mission tempo. The algorithm is designed to keep the UGV a safe distance from the unknown frontier to prevent backtracking. All the algorithms were tested in Gazebo using the ROS framework. The Dijkstra Frontier method was also tested on the hardware system. The results show the RRT Explore algorithm to work well for exploring the environment, performing equally or better than the Dijkstra Frontier method. The UGV partial plan method showed a decreased traveled distance for the UGV but increases in UGV mission time with more conservative distances from danger. Overall, the framework showed a good exploration of the environment and performs the intended missions. / Master of Science / This work presents a framework for the exploration and path planning for a collaborative aerial and ground vehicle robotic system. The system is composed of an aircraft with a camera system for obstacle detection and a ground vehicle with no sensors for obstacle detection. Two exploration algorithms were developed to guide the exploration of the aircraft. Both identify frontiers for exploration with the Dijkstra Frontier method using path planning algorithms to identify a frontier with unknown space (Dijkstra Frontier), and the other uses a sampling based path planning method (RRT Explore) to identify multiple frontiers for selection. The final algorithm developed was for to give the ground vehicle intermediate plans when an entire plan is not yet found. The algorithm is designed to keep the ground vehicle a safe distance from the unknown frontier to prevent backtracking. All the algorithms were tested in a simulation framework using Robot Operating System and one exploration method was tested on the hardware system. The results show the RRT Explore algorithm to work well for exploring the environment, performing equally or better than the Dijkstra Frontier method. The ground vehicle intermediate plan method showed a decreased traveled distance for the ground vehicle but increases in ground vehicle mission time with more conservative distances from danger. Overall, the framework showed a good exploration of the environment and performs the intended missions.

This thesis presents the design and build of tracking system for a quadrotor to chase a moving target based on computer vision in GPS-denied environment. The camera is mounted at the bottom of the quadrotor and used to capture the image below the quadrotor. The image information is transmitted to computer via a video transmitter and receiver module. The target is detected by the color and contour-based detection algorithm. The desired pitch and roll angles are calculated from the position controller based on the relative position and velocity between the moving target and the quadrotor. Interface between PC and quadrotor is built by controlling the PWM signals of the transmitter for command transmission. Three types of position controllers including PD controller, fuzzy controller and self-tuning PD controller based on fuzzy logic are designed and tested in the tracking tests. Results on the corresponding tracking performances are presented. Solutions to improving the tracking performance including the usage of optical sensor for velocity measurement and high-resolution camera for higher image quality are discussed in future work. / Master of Science