TY - GEN
T1 - Using coverage for measuring the effect of haptic feedback in human robotic swarm interaction
AU - Nunnally, Steven
AU - Walker, Phillip
AU - Chakraborty, Nilanjan
AU - Lewis, Michael
AU - Sycara, Katia
PY - 2013
Y1 - 2013
N2 - 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 haptic 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 haptic 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 haptic feedback does not degrade performance in any of the tested environments. This supports our hypothesis that haptic feedback is useful in HSI and requires further research to maximize its potential.
AB - 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 haptic 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 haptic 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 haptic feedback does not degrade performance in any of the tested environments. This supports our hypothesis that haptic feedback is useful in HSI and requires further research to maximize its potential.
UR - https://www.scopus.com/pages/publications/84893603201
U2 - 10.1109/SMC.2013.94
DO - 10.1109/SMC.2013.94
M3 - Conference contribution
AN - SCOPUS:84893603201
SN - 9780769551548
T3 - Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
SP - 516
EP - 521
BT - Proceedings - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
T2 - 2013 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2013
Y2 - 13 October 2013 through 16 October 2013
ER -