This paper discusses advanced human-robot coordination systems. In order to realize the coordination, robots have to behave as not only followers but also leaders when they execute tasks with humans. As an example of the advanced human-robot coordination systems, a male-type dance partner robot is developed, which behaves as a male dancer and executes ballroom dances with a human. In ballroom dances, a male dancer leads a female dancer, and selects the next step based on the information such as the relative position between themselves and other dance couples, their positions in the dance floor, and so on. This paper addresses the step selection problems, which contains collision avoidances with other dance couples. Hidden Markov Models are used to estimate their dance step trajectories. Experiments and simulations are performed to illustrate the validity of the proposed method.