Abstract
A robotic swarm is a decentralized group of robots which overcome failure of individual robots with robust emergent behaviors based on local interactions. These behaviors are not well built for accomplishing complex tasks, however, because of the changing assumptions required in various applications and environments. A new movement in the research field is to add human input to influence the swarm in order to help make the robots goal directed and overcome these problems. This research in Human Swarm Interaction (HSI) focuses on different control laws and ways to integrate the human intent with local control laws of the robots. Previous studies have all used visual feedback through a computer interface to give the user the swarm state information. This study adapted swarm control algorithms to give the operator hap tic feedback as well as visual feedback. The study shows the benefits of the additional feedback in a target searching class. Researchers in multi-robot systems have shown benefits of hap tic feedback in obstacle navigation before, but this study is a novel method because of the decentralized formation of the robotic swarm. In most environments, operators were able to cover significantly more area, increasing the chance of finding more targets. The other environment found no significant difference, showing that the hap tic feedback does not degrade performance in any of the tested environments. This supports our hypothesis that hap tic feedback is useful in HSI and requires further research to maximize its potential.
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