The next frontier of interplanetary exploration missions would encounter countless unpredictable geographical challenges including uninhabitable caves, icy craters of the Moon and Mars, unsustainable mountain cliffs, high radiation areas, and extreme temperature environments. This research will design a fully autonomous and cooperative robotics team composed of unmanned ground vehicles (UGVs) with hybrid operational modes to tackle the multiple traveling salesman problem (mTSP) and to overcome environmental obstacles, to accomplish the challenging interplanetary exploration missions. The hybrid operational modes allow every UGV Firstly, I would like to express my sincere gratitude to my advisor, Dr. Ran Dai for the continuous support of my Honors Undergraduate Research Program, for her patience, motivation, and immense knowledge of robotics, automation, and optimization. Her guidance helped me in all the time of research and writing of this thesis. I could not have imaged having a better advisor and mentor for my Honors Undergraduate Research Program. Because of Dr. Dai, I managed to have my first conference paper submitted to the 2020 International Conference on Robotics and Automation (ICRA) as a first author. Without her strong support, it would not be possible to conduct this research. My sincere thanks also go to Dr. Carlos Castro, who provided me insightful comments and encouragement on being an outstanding presenter as a Buckeye engineering student to prepare me for my Oral Defense. Furthermore, Dr. Castro always willing to listen patiently and to provide advice when I faced unpredictable challenges on my research like a closed labmate of mine quitted the research team out of a sudden. Besides my advisor and Dr. Castro, I would like to thank Raymond Brooks, who is my laboratory supervisor at Department of Engineering Education, and Ali Rahimiardestani, who is my lab partner for giving me an access to use laser-cutting machine and 3D-printers to manufacture my research jumping rovers for free, teaching me the proper methods of operating the laser-cutting machine and 3D-printers and teaching me efficient techniques of soldering my rovers' electronic components. Without my lab supervisor and lab partner guidance and support, it would take me more time and cost me more money to build a team of jumping rovers. iv I thank my fellow Automation and Optimization lab mates, MyungJin Jung, Changhuang Wan, and Isaac Shyu in for the stimulating discussion, for the sleepless night we were working together before deadlines, and for all the fun we had in the last four semesters. Because of their advice, suggestions, encouragement, and constructive criticism, I learned several ingenious heuristic techniques to solve and optimize a path planning problem with MATLAB and run an indoor simulation efficiently with robots and the VICON system used to track the position of objects. Last but not least, I would like to thank my family: my parents, grandparents, my only younger brother and my relatives for supporting me spiritually ...

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This paper demonstrates an innovative group of robots, consisting of jumping rovers and a charging station, improved traversability and extended energy endurance when traveling to multiple target locations. By employing different jumping rovers with distinct energy consumption characteristics and jumping capabilities, we focus on searching for the most energy-efficient path of each jumping rover in a multi-waypoints visiting mission with obstacles. As jumping rovers can jump onto or over some obstacles without navigating around them, they have the potential to save energy by generating alternative paths to overcome obstacles. Moreover, due to the energy demands for the multi-waypoints mission and the limited battery capacity, a charging station is considered to provide extra energy for enhanced endurance during the mission. We first apply a refined rapidly-exploring random tree star (RRT∗) algorithm to find energy-efficient paths between any two target locations. Then, the genetic algorithm (GA) is applied to select the most profitable combination of paths to visit all targets with energy constraints. Finally, we verify the improved mobility and energy efficiency in both virtual simulation and experimental tests using a group of customized jumping rovers with a charging station and the proposed path planning and task allocation method.