 However, limited by reasoning capability and knowledge level , it is challenging for a robot to self diagnose and correct their abnormal behaviors. To solve this problem, a novel method is proposed, human-to-robot attention transfer ( H2R-AT) to seek help from a human . H2R-AT is developed based on \textbf{ \textit{\textbf{  a novel stacked neural networks model, transferring human attention embedded in verbal reminders to robot attention embedded in robot visual perceiving .
<coherence>  However, limited by reasoning capability and knowledge level , it is challenging for a robot to self diagnose and correct their abnormal behaviors. To solve this problem, a novel method is proposed, human-to-robot attention transfer ( H2R-AT) to seek help from a human . H2R-AT is developed based on \textbf{ \textit{\textbf{  a novel stacked neural networks model, transferring human attention embedded in verbal reminders to robot attention embedded in robot visual perceiving .
 However, limited by reasoning capability and knowledge level , it is challenging for robots to self-diagnose and -correct their own abnormality in both planning and executing. To improve robot self diagnosis capability, in this research a novel human-to-robot attention transfer ( H2R-AT) to seek help from a human . H2R-AT is developed based on \textbf{ \textit{\textbf{ a novel stacked neural networks model, transferring human attention embedded in verbal reminders to robot attention embedded in robot visual perceiving .