Dynamic Visual Feedback System Research Articles

Passivity-based visual feedback control with dynamic compensation of mobile manipulators: Stability and [formula omitted]-gain performance analysis

This paper addresses the problem of visual dynamic control based on passivity to solve the target tracking problem of mobile manipulators with eyes-in-hand configuration in the 3D-workspace. The redundancy of the system is used for obstacles avoidance and singular configuration prevention through the system’s manipulability control. The design of the stable control system is based on its passivity properties. A robustness analysis and an L2-gain performance analysis are also presented. Finally, simulation and experimental results are reported to verify the stability and L2-gain performance of the dynamic visual feedback system.

Passivity‐based control on dynamic visual feedback systems with movable camera configuration

AbstractThis paper deals with control of dynamic visual feedback systems with a movable camera configuration. This configuration consists of a robot manipulator and a camera that is attached to the end‐effector of another robot manipulator. This system, which can be interpreted as the dynamic visual feedback system with an eye‐in‐hand configuration and a fixed camera one as a special case, can enlarge the field of view. First, the dynamic visual feedback system with an eye‐to‐hand configuration is given with the fundamental representation of a relative rigid body motion. Second, we construct the dynamic visual feedback system with a movable camera configuration by combining the camera control error system. Next, we derive the passivity of the dynamic visual feedback system. Based on the passivity, stability and L2‐gain performance analysis are discussed. Finally the validity of the proposed control law can be confirmed by comparing the experimental results. © 2009 Wiley Periodicals, Inc. Electron Comm Jpn, 92(6): 1–11, 2009; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecj.10091

Stabilizing Predictive Visual Feedback Control for Fixed Camera Systems

This paper investigates a vision based robot control via a receding horizon control strategy for fixed camera systems, as a stabilizing predictive visual feedback control. Firstly, a 3D dynamic visual feedback system with a fixed camera configuration is reconstructed in order to improve performance of estimation. Next, a stabilizing receding horizon control for the 3D dynamic visual feedback system, a highly nonlinear and relatively fast system, is proposed. The stability of the receding horizon control scheme is guaranteed by using the terminal cost derived from the energy function of the dynamic visual feedback system. Furthermore, simulation and actual nonlinear experimental results are assessed with respect to the stability and the performance.

Passivity-based Control of Dynamic Visual Feedback Systems with Movable Camera Configuration

This paper deals with control of dynamic visual feedback systems with a movable camera configuration. This configuration consists of a robot manipulator and a camera that is attached to the end-effector of another robot manipulator. This system which can be interpreted the dynamic visual feedback system with an eye-in-hand configuration and a fixed camera one as a special case, can enlarge the field of view. Firstly the dynamic visual feedback system with an eye-to-hand configuration is given with the fundamental representation of a relative rigid body motion. Secondly we construct the dynamic visual feedback system with a movable camera configuration by combining the camera control error system. Next, we derive the passivity of the dynamic visual feedback system. Based on the passivity, stability and L2-gain performance analysis are discussed. Finally the validity of the proposed control law can be confirmed by comparing the experimental results.

Predictive Visual Feedback Control with Eye-in/to-Hand Configuration via Stabilizing Receding Horizon Approach

This paper investigates vision based robot control via a receding horizon control strategy for an eye-in/to-hand system, as a predictive visual feedback control. Firstly, the dynamic visual feedback system with the eye-in/to-hand configuration is reconstructed in order to improve the performance of the estimation. Next, a stabilizing receding horizon control for the 3D dynamic visual feedback system, a highly nonlinear and relatively fast system, is proposed. The stability of the receding horizon control scheme is guaranteed by using the terminal cost derived from an energy function of the visual feedback system. Furthermore, simulation results are assessed with respect to the stability and the performance.

Passivity-Based Dynamic Visual Feedback Control for Three-Dimensional Target Tracking: Stability and $L_{2}$-Gain Performance Analysis

This paper investigates vision-based robot control based on passivity for three-dimensional (3-D) target tracking. First, using standard body-attached coordinate frames (the world frame, camera frame, and object frame), we represent the relative position and orientation between a moving target and a camera as an element of SE(3). Using this representation we derive a nonlinear observer to estimate the relative rigid body motion from the measured camera data. We then establish the relationship between the estimation error in a 3-D workspace and in the image plane. We show passivity of the dynamic visual feedback system by combining the passivity of both the visual feedback system and the manipulator dynamics which allows us to prove stability in the sense of Lyapunov for the full 3-D dynamic visual feedback system. The L2 -gain performance analysis, which deals with the disturbance attenuation problem, is then considered via dissipative systems theory. Finally, experimental results are presented to verify the stability and L2-gain performance of the dynamic visual feedback system

PASSIVITY-BASED DYNAMIC VISUAL FEEDBACK CONTROL WITH A MOVABLE CAMERA

This paper deals with the dynamic visual feedback control with a movable camera instead of a fixed camera in the fixed camera configuration. Firstly the brief summary of the visual feedback system with a fixed camera is given with the fundamental representation of a relative rigid body motion. Secondly we construct the new error system in order to consider the camera field of view. Next, we derive the passivity of the dynamic visual feedback system by combining the manipulator dynamics and the visual feedback system. Based on the passivity stability and L2-gain performance analysis are discussed. Finally the validity of the proposed control law can be confirmed by comparing the simulation results.

Observer-based Dynamic Visual Feedback Control of Robotic Systems

This paper considers vision-based motion control with the manipulator dynamics using position measurements and visual information, which we term dynamic visual feedback control. Firstly the visual feedback system of rigid body motion is described in order to derive the dynamic visual feedback system. Secondly we propose a dynamic visual feedback control law which guarantees local asymptotic stability of the overall closed-loop system using a Lyapunov function. L2-gain performance analysis for the proposed control law has been discussed using the energy function which plays the role of a storage function. Next, we show that the control law is based on passivity and the dynamic visual feedback system is constructed from two passive systems. Finally simulation results confirm the effectiveness of the dynamic visual feedback control law.

OBSERVER BASED DYNAMIC VISUAL FEEDBACK CONTROL FOR NONLINEAR ROBOTICS SYSTEMS

This paper investigates a robot motion control problem with visual information. Firstly the model of the relative rigid body motion (positions and rotations) and the method for the estimation of the relative rigid body motion are presented in order to derive the visual feedback system. Secondly we consider the velocity observer and derive the dynamic visual feedback system which contains the manipulator dynamics. Finally the main result with respect to stability for the proposed dynamic visual feedback control is discussed.