This study proposes the bearing-only leader-follower formation control method and examines the nonlinear observability properties of the leader robot system. A study of the nonlinear observability properties between the leader robot and landmarks shows that the system is completely observable when the leader robot can observe four different landmarks. A subsequent study of the leader-follower formation control shows that when the leader robot system satisfies the observability condition of the nonlinear system, the system output can convey sufficient information to allow the observer to provide a correct estimate of the state. Consequently, multi-robots can quickly form and maintain a formation based on the following sufficient bearing-only information, which is that follower robots observe the leader robot. In leader-follower formation, the unscented Kalman filter is employed to estimate the states of the leaderfollower robot system. Based on this system, the input-output feedback control law is executed to control the real-time movement of the followers, which allows the leader-follower formation to be properly maintained. Finally, simulation results are presented to demonstrate that the proposed approach can efficiently control the formation of multi-robots as desired.

This paper develops an adaptive particle filter for indoor mobile robot localization, in which two different resampling operations are implemented to adjust the number of particles for fast and reliable computation. Since the weight updating is usually much more computationally intensive than the prediction, the first resampling-procedure so-called partial resampling is adopted before the prediction step, which duplicates the large weighted particles while reserves the rest obtaining better estimation accuracy and robustness. The second resampling, adopted before the updating step, decreases the number of particles through particle merging to save updating computation. In addition to speeding up the filter, sample degeneracy and sample impoverishment are counteracted. Simulations on a typical 1D model and for mobile robot localization are presented to demonstrate the validity of our approach.

The observability of the leader robot system and the leader-follower formation control are studied. First, the nonlinear observability is studied for when the leader robot observes landmarks. Second, the system is shown to be completely observable when the leader robot observes two different landmarks. When the leader robot system is observable, multi-robots can rapidly form and maintain a formation based on the bearing-only information that the follower robots observe from the leader robot. Finally, simulations confirm the effectiveness of the proposed formation control.

A new formation control method is proposed, which is used to queue multirobots in a single-direction cascade structure. In the cascade formation, each robot is a follower for the previous robot and a leader for the next robot, and the robots in the middle act as both leader and follower. The follower robot can only observe the bearing information of the leader robot. The observability of the cascade leader-follower formation is studied, which shows that the bearing-only observation meets the observability conditions required for the nonlinear system. Based on the bearing-only observations, the unscented Kalman filter (UKF) is employed for the state estimation of the leader and the follower robots at all levels, which enables the real-time movement control of the follower robots via the input-output feedback control. Simulation results demonstrate that the proposed approach can efficiently control the formation of multirobots as desired.