This paper deals with vision-based localization for leader-follower formation control. Each unicycle robot is equipped with a panoramic camera that only provides the view angle to the other robots. The localization problem is studied using a new observability condition valid for general nonlinear systems and based on the extended output Jacobian. This allows us to identify those robot motions that preserve the system observability and those that render it nonobservable. The state of the leader-follower system is estimated via the extended Kalman filter, and an input-state feedback control law is designed to stabilize the formation. Simulations and real-data experiments confirm the theoretical results and show the effectiveness of the proposed formation control.

/pdf/vision-based-localization-for-leader-follower-formation-2pm4vyzyrd.pdf

Vision-Based Localization for Leader–Follower Formation Control

This paper focuses on the localization problem for a mobile camera network. In particular, we consider the case of leader-follower formations of nonholonomic mobile vehicles equipped with vision sensors which provide only the bearing to the other robots. We prove a sufficient condition for observability and show that recursive estimation enables a leader-follower formation if the leader is not trapped in an unobservable configuration. We employ an Extended Kalman Filter for the estimation of each follower position and orientation with respect to the leader and we adopt a feedback linearizing control strategy to achieve a desired formation. Simulation results in a noisy environment are provided.

/pdf/vision-based-localization-of-leader-follower-formations-1lnobmj8dq.pdf

Vision-based Localization of Leader-Follower Formations

This paper focuses on leader-follower formations of mobile robots equipped with panoramic cameras and extend earlier works in the literature addressing both the vision-based localization and control problems. First, a new sufficient analytical condition for localizability is proved and used to shed light on the geometrical meaning of formation localization using uncalibrated vision sensors, here performed with the unscented Kalman filter. Second, we design a feedback control law based on dynamic extension in order to extend the applicability of our control scheme also to the case of distant robots.

/pdf/leader-follower-formations-uncalibrated-vision-based-i060gymlko.pdf

Leader-Follower Formations: Uncalibrated Vision-Based Localization and Control

This paper proposes a single landmark based localization algorithm for non-holonomic mobile robots. In the case of a unicycle robot model, the localization problem is equivalent to the system observability. Based on this observation, the proposed localization method consists in finding a vector function which depends on the measurement vector and its derivatives. In order to compute estimates of the successive derivatives of the measurement vector, we will use a numerical differentiation method. When the robot is able to only measure the relative angle between itself and the landmark in 2D case, the algorithm estimates the posture of the robot, under the hypothesis that control inputs are known. But, sometimes it is also useful to be able to estimate the control input (for example when the robot slips). This is possible with the proposed algorithm by using a landmark in dimension three. The simulation results will be given in order to show the effectiveness of the proposed algorithm. Moreover, these results are compared with those obtained by an Extended Kalman Filter in order to underline the advantages of the new algorithm.

/pdf/a-single-landmark-based-localization-algorithm-for-non-1pkl3aktdz.pdf

A single landmark based localization algorithm for non-holonomic mobile robots

Vision-based control of a robot formation is challenging because the on-board sensor (camera) only provides the view-angle to the other moving robots, but not the distance that must be estimated. In order to guarantee a consistent estimate of the distance by knowing the control inputs and the sensor outputs in a given interval, the nonlinear multi-robot system must preserve its observability. Recent theoretical studies on leader-follower robot formation exploit the interesting influence that the control actions have on observability. Based on these results, in this paper we present a switching active control strategy for formation control. Our control strategy is active in the sense that, while asymptotically achieving the formation control tasks, it also guarantees the system observability in those cases in which all the robots tend to move along non-observable paths. As a result, both estimation and formation performances are improved. Extensive simulation results show the effectiveness of the proposed design.

http://users.ece.gatech.edu/magnus/Papers/MaMaEg_ICRA09.pdf

Fabio Conticelli

Papers

Observability and Nonlinear Observers for Mobile Robot Localization 1