6 papers
Perceive What Matters: Relevance-Driven Scheduling for Multimodal Streaming Perception
Dingcheng Huang, Xiaotong Zhang, Kamal Youcef-Toumi
In modern human-robot collaboration (HRC) applications, multiple perception modules jointly extract visual, auditory, and contextual cues to achieve comprehensive scene understandi…
Towards Scalable Probabilistic Human Motion Prediction with Gaussian Processes for Safe Human-Robot Collaboration
Jinger Chong, Xiaotong Zhang, Kamal Youcef-Toumi
Accurate human motion prediction with well-calibrated uncertainty is critical for safe human-robot collaboration (HRC), where robots must anticipate and react to human movements in…
Eye Movement Feature-Guided Signal De-Drifting in Electrooculography Systems
Lianming Hu, Xiaotong Zhang, Kamal Youcef-Toumi
Electrooculography (EOG) is widely used for gaze tracking in Human-Robot Collaboration (HRC). However, baseline drift caused by low-frequency noise significantly impacts the accura…
Relevance-driven Decision Making for Safer and More Efficient Human Robot Collaboration
Xiaotong Zhang, Dingcheng Huang, Kamal Youcef-Toumi
Human brain possesses the ability to effectively focus on important environmental components, which enhances perception, learning, reasoning, and decision-making. Inspired by this…
Relevance for Human Robot Collaboration
Xiaotong Zhang, Dean Huang, Kamal Youcef-Toumi
Inspired by the human ability to selectively focus on relevant information, this paper introduces relevance, a novel dimensionality reduction process for human-robot collaboration…
Bayesian Intention for Enhanced Human Robot Collaboration
Vanessa Hernandez-Cruz, Xiaotong Zhang, Kamal Youcef-Toumi
Predicting human intent is challenging yet essential to achieving seamless Human-Robot Collaboration (HRC). Many existing approaches fail to fully exploit the inherent relationship…