  The problem of guiding a flock of agents to a destination by the repulsion
forces exerted by a smaller number of external agents is called the shepherding
problem. This problem has attracted attention due to its potential
applications, including diverting birds away for preventing airplane accidents,
recovering spilled oil in the ocean, and guiding a swarm of robots for mapping.
Although there have been various studies on the shepherding problem, most of
them place the uniformity assumption on the dynamics of agents to be guided.
However, we can find various practical situations where this assumption does
not necessarily hold. In this paper, we propose a shepherding method for a
flock of agents consisting of normal agents to be guided and other variant
agents. In this method, the shepherd discriminates normal and variant agents
based on their behaviors' deviation from the one predicted by the potentially
inaccurate model of the normal agents. As for the discrimination process, we
propose two methods using static and dynamic thresholds. Our simulation results
show that the proposed methods outperform a conventional method for various
types of variant agents.
