Current Studies
Adaptive Human-Robot Teaming Architectures
The goal of this study is to evaluate the human robot teaming architectures that can adapt to human workload states (physical, cognitive, auditory, visual and speech workloads) to increase task performance of the team in time sensitive multi-task environment. The architecture uses a combination of machine learning and reinforcement learning algorithms to monitor each of these workload states and adapt the level of assistance provided by the robot accordingly to keep the workload state of the human teammate in the normal range.
If interested, email AHRTLab@gmail.com
Fatigue Estimation
The purpose of this research study is to learn more about the way humans experience fatigue. Our goal is to evaluate a real-time algorithm that can accurately assess human fatigue and that can be used by a robot to adapt its interactions. The algorithm relies on objective fatigue metrics, such as heart rate and respiration rate.
If interested, email ahrtlabhumansub@gmail.com
Request our Data
Please email us at jrheee@rit.edu if you want to use some of our data.