Date of Award:
12-2023
Document Type:
Thesis
Degree Name:
Master of Science (MS)
Department:
Computer Science
Committee Chair(s)
Mario Harper
Committee
Mario Harper
Committee
Steve Petruzza
Committee
Greg Droge
Abstract
There is growing interest in developing autonomous systems capable of exhibiting collaborative behaviors. Using methods such as reinforcement learning is another way to train multiple robots for collaborative task completion. This study was able to successfully in simulation train multiple hexapod robots to push a target to a designated goal collaboratively. This required each robot to learn how find the target and push that target to a goal. This work suggests that using reinforcement learning for collaborative task completion for hexapod robots may simplify the complexity of the software and improve the decisions that they make.
Checksum
c4e43e4fb7013c814405bc6e41f5504e
Recommended Citation
Baker, Tayler Don, "Collaborative Task Completion for Simulated Hexapod Robots Using Reinforcement Learning" (2023). All Graduate Theses and Dissertations, Fall 2023 to Present. 40.
https://digitalcommons.usu.edu/etd2023/40
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