Real-time hand gesture telerobotic system using fuzzy c-means clustering Academic Article uri icon

abstract

  • This paper describes a teleoperation system in which an articulated robot performs a block pushing task based on hand gesture commands sent through the Internet. A Fuzzy C Means clustering method is used to classify hand postures as ¬≥gesture commands". The fuzzy recognition system was tested using 20 trials each of a 12 gesture vocabulary. Results revealed an acceptance rate of 99.6%(percent of gestures with a sufficiently large membership value to belong to at least one of the designated classifications), and a recognition accuracy of 100%(the percent of accepted gestures classified correctly). Performance times to carry out the pushing task showed rapid learning, reaching standard times within 4 to 6 trials by an inexperienced operator.

publication date

  • June 1, 2002