首页|Data on Machine Learning Reported by Researchers at North Dakota State University (Predicting Human Trust In Human-robot Collaborations Using Machine Learning a nd Psychophysiological Responses)
Data on Machine Learning Reported by Researchers at North Dakota State University (Predicting Human Trust In Human-robot Collaborations Using Machine Learning a nd Psychophysiological Responses)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-Current study results on Machine Learn ing have been published. According to news reporting from Fargo, North Dakota, b y NewsRx journalists, research stated, "In the ever-evolving construction indust ry, grappling with challenges such as labor shortages and workplace hazards, hum anrobot collaboration (HRC) has emerged as a transformative solution. However, the industry faces hurdles in comprehending the intricacies of trust dynamics wi thin the domain of HRC." The news correspondents obtained a quote from the research from North Dakota Sta te University, "It exerts considerable influence on both productivity and safety within the construction sector. To address this issue, the paper proposes machi ne learning-based models to predict and enhance human trust in construction robo ts using psychophysiological data. Through a virtual reality bricklaying task ac ross varied construction settings, this study collected psychophysiological data from participants and predicted trust score. Results indicated that electroderm al activity and skin temperature were two significant standalone variables for t rust prediction. With similar R squared value of 0.98, the XG boost, and random forest models displayed superior predictive accuracy, with minor standard deviat ions of 0.003 and 0.004, respectively."
FargoNorth DakotaUnited StatesNort h and Central AmericaCyborgsEmerging TechnologiesMachine LearningRobotRoboticsNorth Dakota State University
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