Jianbo Su

Calibration-free robotic eye-hand coordination based on an auto disturbance-rejection controller

This paper addresses the calibration-free robotic eye-hand coordination in a way other than the conventional image Jacobian matrix approach that has been studied extensively in literature. A nonlinear mapping rather than the linear mapping used in the image Jacobian matrix between the image space and the robotic control space is proposed. This mapping is regarded as the systems unmodeled dynamics expressed in system state equations. An extended state observer is designed first to estimate the unmodeled dynamics as well as the external disturbance of the system. With the estimation results as the compensation, a system controller is designed based on the nonlinear state-error feedback control strategy. Convergence of the extended state observer as well as the overall controller for a typical eye-hand coordination system is proved. Compared with the conventional calibration-free robotic eye-hand coordination with a Jacobian matrix, the proposed controller is independent of specific tasks and system configurations. Thus, a general design procedure is proposed for the calibration-free robotic eye-hand coordination. Simulation and experiment results demonstrate the satisfactory performance and effectiveness of the proposed approach.

Robust Disturbance Observer for Two-Inertia System

This paper proposes a method for designing disturbance observer (DOB) in vibration suppression control of two-inertia system. The key to a vibration suppression control of two-inertia system is eliminating the effect of vibration modes of the plant. For this purpose, feedback controller is designed to cancel the stable vibration modes of plant. However, this cancellation fails due to model error from parameter variations. In this paper, the DOB is employed to compensate for the effect of parameter variations. The Q-filter of DOB is designed with the following specifications: optimal disturbance suppression performance with restricted cutoff frequency; robust stability of closed-loop system against modeling error between the plant and its nominal model; structural restriction of Q-filter itself such as relative order and internal model order. This paper proposes a systematic and straightforward method to attain the above design specifications using standard H∞ control framework. Experimental results verify that the proposed DOB can improve the transient response and effectively suppress the vibration and improve external disturbance removing performance as well.

Online estimation of image Jacobian matrix by Kalman-Bucy filter for uncalibrated stereo vision feedback

This paper studies the visual servoing problem with sensory feedback from uncalibrated stereo cameras. The linear image Jacobian matrix is used to describe the spatial and temporary approximation of the differential movement relation between image space and robotic workspace. We suggest to construct an instrumental dynamic system with state variables formed from elements of the image Jacobian matrix. Thus a Kalman-Bucy filter is used to estimate the state variables of the constructed system online, which is robust to system noise and external disturbances. A 3D tracking task by a robot manipulator with visual feedback from uncalibrated stereo cameras is exemplified to show the formation of the instrumental system, estimation process and performance of the image Jacobian matrix and the design of the servo controller. Effectiveness of the proposed method and satisfactory tracking process can be found from extensive simulations and experiments provided in the paper.

Task-independent robotic uncalibrated hand-eye coordination based on the extended state observer

This paper proposes a standard method to approach the uncalibrated robotic hand-eye coordination problem that is system configuration- and task-independent. The unknown hand-eye relationship is first modeled as the modeling errors of a dynamic system. An extended state observer is then implemented to estimate summation of the systems modeling error and the systems external disturbances. With the estimation results as the compensation, the system control is accomplished from a nonlinear combination of the system state errors. A universal framework of controller design is provided for decoupled and coupled hand-eye systems of different configurations to execute dynamic tracking task.

Motion Compression for Telepresence Locomotion

A telepresence system enables a user in a local environment to maneuver in a remote or virtual space through a robotic operator (agent). In order to ensure a high degree of telepresence realism, it is critical that the local user has the ability to control the remote agents movement through the users own locomotion. The required motion of the remote agent is determined according to its environment and the specific task it is to perform. The local users environment is usually different from that of the remote agent in terms of the shapes and dimensions. A motion mapping is needed from the remote agent to the local user to ensure the similarity of the paths in the two environments. In particular, the terminal position of the local user after a segment of movement is also an important portion in such a motion mapping. This paper progressively addresses these issues from the optimization point of view. Two strategies are suggested for solving the motion mapping problem for the single user case. The resulting solutions are then extended to the multiuser case where several local users share a local environment to control different remote agents. Extensive simulations and comparisons show the feasibility and effectiveness of the proposed approaches.

Design of a Disturbance Observer for a Two-Link Manipulator With Flexible Joints

This brief proposes a method for designing a disturbance observer (DOB) to decouple joint interactions in robot dynamics with nonlinearity. The traditional DOB based on filter design theory has limited performance since the cut-off frequency of its Q-filter is the only tunable parameter to deal with disturbance suppression and model uncertainty. In this brief, a robust optimal design method is developed for the DOB, which can achieve optimal performance of suppressing disturbance by systematically shaping its Q-filter. Simulation results of application to a two-link manipulator with flexible joints show the improvements in disturbance suppression, which illustrates the validity of the proposed method.

Robust Disturbance Rejection Control for Attitude Tracking of an Aircraft

This brief proposes a disturbance rejection control strategy for attitude tracking of an aircraft with both internal uncertainties and external disturbances. The proposed control strategy consists of a robust disturbance observer (DOB) and a nonlinear feedback controller. Specifically, a robust DOB is proposed to compensate the uncertain rotational dynamics into a nominal plant, based on which a nonlinear feedback controller is implemented for desired tracking performance. We first divide the practical rotational dynamics into the nominal part, external disturbances, and equivalent internal disturbances. Then, property of equivalent internal disturbances is explored for stability analysis. A robust DOB is optimized based on H∞ theory to guarantee disturbance rejection performance and robustness against system uncertainties. A practical nonlinear feedback controller is hence applied to stabilize the compensated system based on backstepping approach. Experiments on a quadrotor testbed show that the proposed robust DOB can suppress the external disturbances and measurement noise, with the robustness against system uncertainties.

Motion Planning and Coordination for Robot Systems Based on Representation Space

This paper proposes a general motion planning and coordination strategy for robot systems. The representation space (RS) of a robot system is constructed to describe the distributions of system attributes. The reachable area in the RS, denoting the attribute set that the system can be of, indicates the systems ability to accomplish tasks. Moreover, it also describes the influences of the internal and external constraints on the systems capability. Task realization is transformed to finding a trajectory in the RS for the system attributes to transit along under constraints. Meanwhile, the realizable conditions of a prescribed task by the robot system of specific configurations are discussed. If the task is realizable, the optimal strategy for task execution could further be figured out. Otherwise, it could be transformed to be realizable via task reassignment or system reconfigurations so that a connected path could be found for the transition of the system attributes from the starting point to the goal in the RS. The proposed scheme contributes to designing, planning, and coordination of the robotic tasks. Experiments on path planning of a robot manipulator and formation movement of a multirobot system, as well as coordination of a mobile manipulator system, are conducted to show the validity and generalization of the proposed method.

Incremental learning with balanced update on receptive fields for multi-sensor data fusion

This paper addresses multi-sensor data fusion with incremental learning ability. A new cost function is proposed for the receptive field weighted regression (RFWR) algorithm based on the idea of back propagation (BP), so that the computation efficiency and the learning strategy of the modified RFWR are much more applicable for multi-sensor data fusion problem. Thus a new fusion structure and algorithm with incremental learning ability is constructed by adopting the modified RFWR algorithm together with the weighted average algorithm. Experiments of a two-camera unified positioning system are implemented successfully to test the proposed computation structure and algorithms.

Disturbance rejection control for non-minimum phase systems with optimal disturbance observer.

This paper investigates the disturbance rejection control for stable non-minimum phase (NMP) systems with time delay. A robust disturbance observer (DOB) based control structure is proposed. Specifically, the robust DOB is employed to compensate the uncertain plant into a nominal one, based on which a prefilter is adopted to acquire desired performance. Then, a novel DOB configuration strategy for stable NMP systems is proposed. This strategy synthesizes the internal and robust stability, relative order and mixed sensitivity design requirements together to establish the optimization function. The optimal solution is obtained by standard H∞ theory under the condition of guarantying the presented requirements. We also investigate how the DOB can compensate the uncertain plant into a nominal one. The specifical design procedure is presented for an uncertain plant with both unstable zeros and time delay.