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The purpose of this paper is to solve the ground verification and test method for space robot system capturing the target satellite based on visual servoing with time-delay in 3-dimensional space prior to space robot being launched.

To implement the approaching and capturing task, a motion planning method for visual servoing the space manipulator to capture a moving target is presented. This is mainly used to solve the time-delay problem of the visual servoing control system and the motion uncertainty of the target satellite. To verify and test the feasibility and reliability of the method in three-dimensional (3D) operating space, a set of ground hardware-in-the-loop simulation verification systems is developed, which adopts the end-tip kinematics equivalence and dynamics simulation method.

The results of the ground hardware-in-the-loop simulation experiment validate the reliability of the eye-in-hand visual system in the 3D operating space and prove the validity of the visual servoing motion planning method with time-delay compensation. At the same time, owing to the dynamics simulator of the space robot added in the ground hardware-in-the-loop verification system, the base disturbance can be considered during the approaching and capturing procedure, which makes the ground verification system realistic and credible.

The ground verification experiment system includes the real controller of space manipulator, the eye-in-hand camera and the dynamics simulator, which can veritably simulate the capturing process based on the visual servoing in space and consider the effect of time delay and the free-floating base disturbance.

The purpose of this paper is to solve the tracking problem for free-floating space manipulators (FFSMs) in task space with parameter uncertainties and external disturbance.

In this paper, the novel cerebellar model articulation controller (CMAC) is designed with the feedback controller. More precisely, the parameter uncertainties in the FFSM are considered for achieving the robustness.

By using the dynamically equivalent model, the CMAC can be designed and trained with the desired performance, such that the prescribed trajectory can be followed accordingly. The simulation results are presented for illustrating the validity of the derived results.

Based on the designed CMAC, the tracking error would be approaching zero by choosing appropriate quantization level in CMAC and the corresponding learning rules can be tuned online.

Rapid satellite capture by a free-floating space robot is a challenge problem because of no-fixed base and time-delay issues. This paper aims to present a modified target capturing control scheme for improving the control performance.

For handling such control problem including time delay, the modified scheme is achieved by adding a delay calibration algorithm into the visual servoing loop. To identify end-effector motions in real time, a motion predictor is developed by partly linearizing the space robot kinematics equation. By this approach, only ground-fixed robot kinematics are involved in the predicting computation excluding the complex space robot kinematics calculations. With the newly developed predictor, a delay compensator is designed to take error control into account. For determining the compensation parameters, the asymptotic stability condition of the proposed compensation algorithm is also presented.

The proposed method is conducted by a credible three-dimensional ground experimental system, and the experimental results illustrate the effectiveness of the proposed method.

Because the delayed camera signals are compensated with only ground-fixed robot kinematics, this proposed satellite capturing scheme is particularly suitable for commercial on-orbit services with cheaper on-board computers.

This paper is original as an attempt trying to compensate the time delay by taking both space robot motion predictions and compensation error control into consideration and is valuable for rapid and accurate satellite capture tasks.

This study aims to design a controller which can improve the end-effector low-frequency chattering resulting from the measurement noise and the time delay in the on-orbit tasks. The rendezvous point will move along the rendezvous ring owing to the error of the camera, and the manipulators’ collision need be avoided. In addition, owing to the dynamics coupling, the manipulators’ motion will disturb the spacecraft, and the low tracking accuracy of the end-effector needs to be improved.

This paper proposes a minimum disturbance controller based on the synchronous and adaptive acceleration planning to improve the tracking error and the disturbance energy. The synchronous and adaptive acceleration planning method plans the optimal rendezvous point and designs synchronous approaching method and provides an estimation method of the rendezvous point acceleration. A minimum disturbance controller is designed based on the energy conservation to optimize the disturbance resulting from the manipulator’s motion.

The acceleration planning method avoids the collision of two end-effectors and reduces the error caused by the low-frequency chattering. The minimum disturbance controller minimizes the disturbance energy of the manipulators’ motion transferred to the spacecraft. Experiment results show that the proposed method improves the low-frequency chattering, and the average position tracking error reduces by 30%, and disturbance energy reduces by 30% at least. In addition, it has good performances in the synchronous motion and adaptive tracking.

Given the immeasurability of the target satellite acceleration in space, this paper proposes an estimation method of the acceleration. This paper proposes a synchronous and adaptive acceleration planning method. In addition, the rendezvous points are optimized to avoid the two end-effectors collisions. By the energy conservation, the minimum disturbance controller is designed to ensure a satisfying tracking error and reduce the disturbance energy resulting from the manipulators’ motion.

This paper is concerned with the repetitive trajectory tracking control for space manipulators under model uncertainties and vibration disturbances.

The model uncertainties and link vibration of manipulators will degrade the tracking performance of space manipulators; in this paper, a new hybrid control scheme that consists of a composite hierarchical anti-disturbance controller and an iterative learning controller is developed to solve this problem.

The composite hierarchical controller can effectively attenuate model uncertainties and reject vibration disturbances, whereas the iterative learning controller is able to improve the tracking accuracy for repetitive reference trajectory.

The proposed scheme compensates for the shortcomings of iterative learning control which can only deal with repetitive disturbances, ensuring the accuracy and repeatability of space manipulators under model uncertainties and random disturbances.

The purpose of this paper is to develop a set of ground experiment system to verify the basic functions of space effector and the capturing reliability of space end-effector for the free-floating target payload in the three-dimensional space. The development of ground experiment system for space end-effector is essential and significant, because it costs too much to launch a space robot or other spacecraft and carry out operation tasks in space. Owing to the negligible gravity in space, which is different from that in the ground environment, ground experiment system for space end-effector should have the capability of verifying the basic functions of space effector and the reliability of space end-effector in capturing the free-floating target payload in space.

The ground experiment system for space end-effector mainly adopts the hybrid simulation method, which includes the real hardware experiment and software simulation. To emulate the micro-gravity environment, the contact dynamics simulator is applied to emulating the motion state of the free-floating target payload, while the admittance control is used to realize the “soft” capturing of space end-effector to simulate the real situation in space.

With the gravity compensation, the influence of gravity is almost eliminated and the results meet the requirements of the experiment. In the ground experiment, the admittance control is effective and the actual motion state of space end-effector capturing the target in space can be simulated. The experiment results show that space end-effector can capture the free-floating target payload successfully and hopefully have the ability to capture a free-floating target in space.

The system can verify space end-effector capturing the free-floating target payload in three-dimensional space and imitate the motion of space end-effector capturing the free-floating target in space. The system can also be modified and improved for application in the verification of space robot capturing and docking the target, which is valuable for the ground verification of space applications.

The purpose of this paper is to present a visual servo tracking strategy for the wheeled mobile robot, where the unknown feature depth information can be identified simultaneously in the visual servoing process.

By using reference, desired and current images, system errors are constructed by measurable signals that are obtained by decomposing Euclidean homographies. Subsequently, by taking the advantage of the concurrent learning framework, both historical and current system data are used to construct an adaptive updating mechanism for recovering the unknown feature depth. Then, the kinematic controller is designed for the mobile robot to achieve the visual servo trajectory tracking task. Lyapunov techniques and LaSalle’s invariance principle are used to prove that system errors and the depth estimation error converge to zero synchronously.

The concurrent learning-based visual servo tracking and identification technology is found to be reliable, accurate and efficient with both simulation and comparative experimental results. Both trajectory tracking and depth estimation errors converge to zero successfully.

On the basis of the concurrent learning framework, an adaptive control strategy is developed for the mobile robot to successfully identify the unknown scene depth while accomplishing the visual servo trajectory tracking task.

The purpose of this paper is to present the radial basis function (RBF) networks‐based adaptive robust control for an omni‐directional wheeled mobile manipulator in the presence of uncertainties and disturbances.

First, a dynamic model is obtained based on the practical omni‐directional wheeled mobile manipulator system. Second, the RBF neural network is used to identify the unstructured system dynamics directly due to its ability to approximate a nonlinear continuous function to arbitrary accuracy. Using the learning ability of neural networks, RBFNARC can co‐ordinately control the omni‐directional mobile platform and the mounted manipulator with different dynamics efficiently. The implementation of the control algorithm is dependent on the sliding mode control.

Based on the Lyapunov stability theory, the stability of the whole control system, the boundedness of the neural networks weight estimation errors, and the uniformly ultimate boundedness of the tracking error are all strictly guaranteed.

In this paper, an adaptive robust control scheme using neural networks combined with sliding mode control is proposed for crawler‐type mobile manipulators in the presence of uncertainties and disturbances. RBF neural networks approximate the system dynamics directly and overcome the structured uncertainty by learning. Based on the Lyapunov stability theory, the stability of the whole control system, the boundedness of the neural networks weight estimation errors, and the uniformly ultimate boundedness of the tracking error are all strictly guaranteed.

The purpose of this paper is to present the design and experiment of a universal space-saving end-effector for multi-task operations.

The universal end-effector is equipped with capture and actuation transmission capabilities with two corresponding subsystems, which are highly integrated systems of mechanics, electronics and sensors. A trefoil-shaped capture system is developed for closed envelop. The worm gear pair is adopted for self-locking and space-saving, and it is used in a unique manner for three grapple chains’ synchronous motion. The combination of optimal straight path linkage and pantograph mechanism is proposed in the transmission system. The electrical structure and the multi-sensory system provide the foundation for control strategy.

Simulations and experiments demonstrated characteristics of the universal end-effector. The compliance of the manipulator guaranteed the achievement of “soft capture” by the end-effector. Due to the self-locking property, the end-effector and the grapple interface could keep rigid connection when powered off.

The design process takes practical requirements into consideration. Through experiments, it is proved that the proposed end-effector can be used for the multi-task operations with corresponding tools.

Among end-effectors with operation function, the misalignment tolerance (MT) is originally regarded as a key factor. The adoptions of the worm gear pair and the linkage make it space-saving compared to conventional designs.

The finite-time visual servoing control problem is considered for dynamic wheeled mobile robots (WMRs) with unknown control direction and external disturbance.

By using finite-time control method and switching design technique.

First, the visual servoing kinematic WMR model is developed, which can be converted to the dynamic chained-form systems by using a state and input feedback transformation. Then, for two decoupled subsystems of the chained-form systems, according to the finite-time stability control theory, a discontinuous three-step switching control strategy is proposed in the presence of uncertain control coefficients and external disturbance.

A class of discontinuous anti-interference control method has been presented for the dynamic nonholonomic systems.