The very first classification of causes of errors in the human -
robot system has been presented in this paper. This new model
of error classification in the human - robot system has a global
character. This means that it includes the causes of the errors
of the individual components of the system, but also the errors
that result from their interaction.The model also includes all the
factors surrounding this system, which can act as the cause of
errors in the human - robot system. This model distinguishes
five main groups of causes of errors, described in the paper. The
classification of errors in the human - robot system has great
importance. It can serve to designers as a guide or reminder
on factors that should be taken into account during designing,
in order to reduce the errors in the human - robot system. In
addition, this model can serve to assess the efficiency and possible
causes of accidents in the human - robot system. Certain general
solutions for the reduction of causes of errors in the human -
robot system are also presented
