Motion Planning and Task Allocation for a Jumping Rover Team

Abstract

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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Path Planning for a Jumping Rover Team With a Charging Station in Multi-Waypoints Visiting Missions

“…Based on our prior work of jumping rovers (Tan et al, 2020), this work extends the jumping rover team with a charging station and proposes new algorithms for path planning and task allocation. We first find energy-efficient path segments between any two target locations by a refined RRTp algorithm, where an obstacle can be treated as a possible pathway if a jumping rover is able to jump over it.…”

“…When considering the charging station and energy constraints of each jumping rover, it makes the path planning of the multi-waypoints traveling mission much more challenging, which requires a new formulation and path planning method incorporating the charging function and energy constraints. Compared to our prior work in (Tan et al, 2020), the contribution of this paper includes the following points: (1) a new formulation of the multi-waypoints traveling mission of a robot team integrating the charging function and energy constraints. (2) a path planning algorithm with refined paths that consider more complicated geometries of an obstacle in both rolling and jumping motion, (3) introducing GA to determine both visiting and charging sequences, and (4) design and construction of a charging system that automatically docks with the jumping rovers.…”