Visual servoing with nonlinear observer

Visual servo system is a robot control system which incorporates the vision sensor in the feedback loop. Since the robot controller is also in the visual servo loop, compensation of the robot dynamics is important for high speed tasks. Moreover estimation of the object motion is necessary for real time tracking because the visual information includes considerable delay. This paper proposes a nonlinear model-based controller and a nonlinear observer for visual servoing. The observer estimates the object motion and the nonlinear controller makes the closed loop system asymptotically stable based on the estimated object motion. The effectiveness of the observer-based controller is verified by simulations and experiments on a two link planar direct drive robot</p

An Indirect Adaptive Control Approach to Image Based Visual Servoing for Translational Trajectory Tracking

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Visual servoing with linearized observer

One of the most important problems in feature-based visual servoing is the slow sampling rate and the delay of the camera that can make the closed loop system oscillative or unstable easily. In the paper, a linearized observer that estimates the object velocity and updates the visual information with the joint sampling rate is proposed. Stability of the observer-based control system and effectiveness of the observer are verified by experiments on a PUMA 560 robot</p

Visual Servoing of a UGV from a UAV using Differential Flatness

In this paper the problem of controlling the motion of a nonholonomic vehicle along a desired trajectory using observations from an overhead camera is considered. The control problem is formulated in the image plane. We show that the system in the image plane is differentially flat and use this property to generate effective control strategies using only visual feedback. Simulation results illustrate the methodology and show robustness to errors in the camera calibration parameters

Fault estimation and accommodation for virtual sensor bias fault in image-based visual servoing using particle filter

This study develops a fault estimation and accommodation scheme for the image-based visual servoing (IBVS) system to eliminate the effects of the faults due to the image feature extraction task, which is named as bias virtual sensor fault. First, a bias virtual sensor fault in visual servoing is declared. Then, fault diagnosis (FD), which includes fault detection, isolation and estimation, is designed based on the means of particle filter (PF). Finally, a fault accommodation law is developed based on the information obtained from the fault estimation to compensate for the effects of the fault in the system. The proposed fault estimation and accommodation is verified through simulation and experimental studies, and the results show that the system can estimate and eliminate the unknown fault effects effectively