Dual Quaternion Visual Servo Control

Abstract

This paper focuses on a dual quaternion-based estimation and control approach for position-based visual servoing (PBVS). The pose estimation of the camera is achieved using a dual quaternion-based Extended Kalman Filter (EKF), which estimates the position and orientation of the camera based on feature points acquired through a sequence of camera images. Based on the estimation, a dual quaternion control law is developed to regulate the camera to the desired pose. Leveraging the local exponential stability of the EKF and the global exponential stability of the designed controller, a nonlinear separation principle is used to prove the stability of the joint estimation and control for PBVS. The method is distinguished from other PBVS methods in the sense that a compact representation of dual quaternion is used to represent the pose, and a joint stability of estimator and controller for PBVS in dual quaternion space is presented. The proposed dual quaternion PBVS method is validated using a simulation.