Space Robot Research Articles

Development of 6DOF Hardware-in-the-Loop Ground Testbed for Autonomous Robotic Space Debris Removal

This paper presents the development of a hardware-in-the-loop ground testbed featuring active gravity compensation via software-in-the-loop integration, specially designed to support research in autonomous robotic removal of space debris. The testbed is designed to replicate six degrees of freedom (6DOF) motion maneuvering to accurately simulate the dynamic behaviors of free-floating robotic manipulators and free-tumbling space debris under microgravity conditions. The testbed incorporates two industrial 6DOF robotic manipulators, a three-finger robotic gripper, and a suite of sensors, including cameras, force/torque sensors, and tactile tensors. Such a setup provides a robust platform for testing and validating technologies related to autonomous tracking, capture, and post-capture stabilization within the context of active space debris removal missions. Preliminary experimental results have demonstrated advancements in motion control, computer vision, and sensor fusion. This facility is positioned to become an essential resource for the development and validation of robotic manipulators in space, offering substantial improvements to the effectiveness and reliability of autonomous capture operations in space missions.

Dual-Arm Space Robot On-Orbit Operation of Auxiliary Docking Prescribed Performance Impedance Control

The impedance control of a dual-arm space robot in orbit auxiliary docking operation is studied. First, for the closed-chain hybrid system formed by the dual-arm space robot after capture operation, the dynamic equation of position uncontrolled and attitude controlled is established. The second-order linear impedance model and second-order approximate environment model are established for the problem of simultaneous output force/pose control of the end of the manipulator. Then, aiming at the transient performance control requirements of the dual-arm space robot auxiliary docking operation in orbit, a sliding mode controller with equivalent replacement of tracking errors is designed by introducing Prescribed Performance Control (PPC) theory. Next, Radial Basis Function Neural Networks (RBFNN) are used to accurately compensate for the modeling uncertainties of the system. Finally, the stability of the system is verified by Lyapunov stability determination. The simulation results show that the attitude control accuracy is better than 0.5°, the position control accuracy is better than 10−3 m, and the output force control accuracy is better than 0.5 N when it reaches 30 N. It also indicated that the proposed control algorithm can limit the transient performance of the controlled system within the preset range and achieve high-precision force/pose control, which ensures a more stable on-orbit auxiliary docking operation of the dual-arm space robot.

Model predictive control for space robot manipulator modeled by switched systems: A data‐driven approach

AbstractThis article investigates the data‐driven based model predictive control (MPC) problem for a class of space robot manipulator (SRM). First, the SRM system is modeled as a class of discrete‐time switched system to reflect more system characteristics. Second, only the input‐state data are used for end‐to‐end controller design, and the system identification process is avoided. In order to meet the real‐time requirements of the manipulator arm angles, a kind of constrained predictive control method is designed to prevent the overheating or damage of SRM motor, optimizing the cost function for each decision cycle under the safe control input constraints. Then, based on the average dwell time method, the asymptotic stability is assured for the presented SRM system. The design conditions for data‐driven based MPC are provided in the form of linear matrix inequalities. Finally, the effectiveness and advantage for the developed data‐driven based MPC strategy are validated via a case study of SRM system.

Development of a Mathematical Model of a Highly Maneuverable Robot for Simulation of Robots with Different Types of Designs

The article presents the results of developing a mathematical model and simulation modeling of a three-wheeled highly maneuverable mobile robot. A mathematical model of the robot in the state space has been developed. The possibility of using this robot with rotary modules for analyzing and testing control algorithms for robots of various designs has been considered. The relevance of the study is justified by the high costs of creating physical models of robots for experimental verification of control algorithms. The proposed three-wheeled mobile robot with rotary modules, where each wheel is simultaneously both a driving and a steering wheel, allows reducing these costs, while maintaining the ability to simulate part of the real operating conditions. Simplified diagrams of the robot are given, the main parameters and equations characterizing the change in linear and angular velocity are described. Particular attention is paid to modeling various types of robot drives: automotive type and with a differential drive. In the discrete state space, equations describing the dynamics of the robot were presented, which allows them to be used in software products for modeling. The results of simulation modeling obtained in the SimInTech software environment confirm the effectiveness of the proposed model. The analysis of the obtained results showed that the use of a three-wheeled robot with rotary modules allows successfully simulating the behavior of robots with other types of drives and creating conditions close to real ones for testing control algorithms. The proposed model can be used to improve the quality of design and testing of control algorithms in robotics, while reducing the costs of creating physical models of robots, as well as in the educational process.

Continuous Signal Convolution Using FFT with Overlap for Transportation Robot Coordinate Determination

The paper discusses the development of a continuous discrete signal convolution algorithm using fast Fourier transform (FFT) with overlap for more accurate determination of the coordinates of a transportation robot. Two methods for determining the coordinates of a transportation robot in two-dimensional space are presented, where the convolution operation is used and where this algorithm can be applied. The algorithm is based on a method that allows the FFT to be performed on multiple computational units in parallel, such as on a TMS320F28377D digital signal processor, where three computational units are available that operate independently in parallel. The use of a FFT with overlap allows signal processing without data loss, which is critical for continuous signal processing.The study of the influence of the FFT window offset value on the frequency of obtaining the spectrum of the signal has been carried out, and as it was found that reducing the FFT window offset leads to an increase in the frequency of obtaining the spectrum of the signal, which, in turn, allows you to more accurately restore the amplitude of the original signal, that is, there is less loss of spectrum data. As results, the paper provides illustrations of the study in the form of three-dimensional graphs, where the spectra of the signal in time during the FFT with overlap, where as the initial signal is used a sinusoidal signal, which over time increases its frequency. Comparison of the results of the algorithm without overlap and with overlap at different offset values showed that the method with overlap provides significantly more accurate and frequent acquisition of spectrum data, avoiding data loss.The presented results are useful in robotics when it is required to accurately determine the coordinates of a transportation robot.

Coordinated base disturbance and Cartesian stiffness optimization of a cable-driven redundant space robot

Coordinated base disturbance and Cartesian stiffness optimization of a cable-driven redundant space robot

Trajectory control in redundant space robot systems: a comparative evaluation of various float mechanisms

Trajectory control in redundant space robot systems: a comparative evaluation of various float mechanisms

Dynamic modelling and a model-based control strategy of joint servo system for power transmission line inspection robot

Abstract The time-varying load inertia is one of the important dynamic characteristics of the power transmission line inspection robots (PTLIRs) in joint space, which can heavily affect the stability of the robot in the inspection process. In this paper, with considering the time-varying characteristics of load inertia, a method for modelling and control of the flexible joint servo system of the PTLIR is studied. First, the control system of the PTLIR is established based on the two inertia system. In order to calculate the load inertia, a dynamic model of the inspection robot is established. Then, the model-based notch filter is designed to improve dynamic performance of the robot, and suppress the vibration amplitude change which caused by the time-varying load inertia. Finally, the comparison of the control performance between the traditional control strategy and the model-based control strategy with notch filter are compared. The simulation results show that the paper can provide an effective tool for modelling and improving the stability of the PTLIR.

Joint acceleration based adaptive reactionless manipulation of closed-loop multi-arm space robot in post-capture phase

Joint acceleration based adaptive reactionless manipulation of closed-loop multi-arm space robot in post-capture phase

Enhancing Robot End‐Effector Trajectory Tracking Using Virtual Force‐Tracking Impedance Control

This article presents an extended Cartesian space robot control framework that features a virtual force tracking impedance control to enhance the end‐effector trajectory tracking performance. Initially, the concept of a virtual surface is introduced, which is assumed to be at some constant distance from the desired end‐effector trajectory. This virtual surface generates a virtual contact force when interacting with the torque‐controlled robot end‐effector. The interaction is then manipulated using an impedance control model to track a constant desired force. If the robot end‐effector deviates from the desired trajectory, the constant force‐tracking impedance control generates a compliance trajectory that regulates the end‐effector movements, constraining it to the desired trajectory. For robust force tracking, impedance parameters are optimally tuned using a closed‐loop dynamic model incorporating both robot and impedance dynamics. Additionally, super twisting sliding mode control (STSMC) is integrated to overcome uncertainties and the impact of robot dynamics on force‐tracking performance. Experimental validation confirms the theoretical claims of the proposed approach. It demonstrates that force‐tracking impedance control improves the end‐effector trajectory tracking by quickly reacting to the dynamic trajectories compared to position control only and effectively maintains it on the desired trajectories.

Expressing Anger with Robot for Tackling the Onset of Robot Abuse

Service robots in public spaces can sometimes become victims of ‘abuse’, manifesting as persistent blocking of the robot’s path, physical violence such as pushing or pulling, or abusive language. This kind of abuse can be a serious obstacle to the deployment of robots. We studied the possibility of mitigating obstructive behaviour towards the robot, which is known to happen in the early stages of robot abuse, by having the robot express anger-like emotions. We identified and implemented three distinct anger behaviours: furious, quiet, and scolding anger. Through an online video survey, we confirmed that all three designed robot behaviours were perceived as expressions of anger. Finally, we ran an in-lab experiment with child participants to study the influence of the robot’s expressions of anger on children’s obstructive behaviours. The results show that ‘furious anger’ was effective in reducing the frequency of obstructions, whereas the other two anger types were not.

Tracking control and neural network disturbance observer for a 6 DoF underwater welding robot

This article addresses the control of an underwater welding robot in 3D space. A control approach combining a finite time sliding mode controller for position and orientation control and feedback linearization for controlling one degree of freedom of the welding arm is adopted. The utilization of underwater robots in marine environments is often hindered by uncertainties and disturbances induced by ocean waves and currents, resulting in decreased accuracy and operational disruptions. To overcome these challenges, a novel observer based on a radial basis function neural network is developed to enhance the performance of the underwater welding robot. The neural network’s weights are optimized using the Lyapunov method within the control law framework. Through simulations, the article evaluates the observer’s efficacy in accurately tracking reference trajectories in the presence of uncertainties. The results underscore the significant contribution of this estimator in mitigating uncertainties and disturbances, thereby substantially improving the overall performance and operational reliability of underwater welding robots. The control strategies and observer design presented in this study pave the way for enhanced accuracy, stability, and efficiency in complex underwater welding operations.

Evaluation on Numerical Method of Differential Formula Based on Optimal Control of Space Robot's Attitude and Motion

Evaluation on Numerical Method of Differential Formula Based on Optimal Control of Space Robot's Attitude and Motion

Motion planning of free-floating space robots for tracking tumbling targets by two-axis matching via reinforcement learning

The increasing amount of space debris poses a persistent threat to the safety of spacecraft. These non-cooperative targets are generally in a tumbling state, which places stringent requirements on the precision of the end-effector pose for capture tasks. Moreover, there are still difficulties in exploring the orientation state space, making it impractical to track targets with complex tumbling states based on reinforcement learning. To track tumbling targets quickly with high accuracy, we propose Two-Axis Matching Path Tracking (TMPT) algorithm. Our algorithm reduces the complexity of orientation exploration and improves the convergence speed through two-axis matching and the self-guidance module. Furthermore, the training environment has been redesigned by adopting staged tumbling target environment, which expands the range of trackable targets. Comparative simulation results demonstrate the efficiency and robustness of the algorithm.

IEEE Transactions on Field Robotics Call for Special Issue on Space Robotics [Society News

<i>IEEE Transactions on Field Robotics</i> Call for Special Issue on Space Robotics [Society News

Predefined-time sliding mode position and attitude coupling control for in-cabin robots on space stations

As space science advances, the significance of space robotics research escalates, particularly in control methodologies. Addressing the work efficiency requirements during the mission of the in-cabin robot, it is necessary to develop a fast and robust position and attitude coupling controller for in-cabin robots. This paper presents a predefined-time sliding mode position and attitude coupling control method, employing the SE(3) frame description. The first, the dynamic model of the in-cabin robot is developed within the SE(3) framework. Then, the predefined-time position and attitude coupling sliding mode controller is designed with a sliding surface based on the dynamic error model, and a hyperbolic tangent function is used to suppress system chattering. In addition, the stability of the proposed control method is rigorously confirmed using the Lyapunov theorem, ensuring that the convergence time is accurately predefined. Finally, simulation results are provided to demonstrate the effectiveness of this novel control strategy. A comparative analysis with fixed-time sliding mode control highlights its superior performance.

A Comparative Study on Human Space Flights over Robotic Space Missions and Habitation involved in the Human Space Mission

A Comparative Study on Human Space Flights over Robotic Space Missions and Habitation involved in the Human Space Mission

Continuous-discrete extended Kalman filter based parameter identification method for space robots in postcapture

Continuous-discrete extended Kalman filter based parameter identification method for space robots in postcapture

Multi-Level Behavioral Mechanisms and Kinematic Modeling Research of Cellular Space Robot

The cellular space robot (CSR) is a new type of self-reconfigurable robot. It can adapt the variety of on-orbit service tasks with large space spans through multi-level reconfiguration mechanisms. As the CSR has a large configuration space, kinematic solving becomes a key problem affecting on-orbit operation capability, and kinematic automatic solving research must be conducted. In order to solve this problem, firstly, the cellular space robot system capable of realizing multi-level self-reconfiguration is proposed for the demand of space on-orbit service, and the kinematic equations of modules are constructed by considering a single module function using screw theory. Secondly, the kinematics of the cellular space robot are encapsulated and divided into multiple levels, and the multilevel-assembly relationship-description method for robotic systems is proposed based on graph theory. On this basis, the pathway-solving algorithm is proposed to express the robot organization reachability information. Finally, the module–organ–robot multilevel kinematics solving algorithm is proposed in combination with screw theory. In order to verify the effectiveness of the algorithm in this paper, numerical simulation is used to compare with the proposed algorithm. The results show that compared with the traditional algorithm, the method in this paper only needs to update part of the assembly relations after organ migration, which simplifies the kinematic modeling operation and improves the efficiency of kinematic computation.

Deep Koopman-operator-based model predictive control for free-floating space robots with disturbance observer

This paper investigates the optimal tracking control problem of free-floating space robots in the presence of non-ideal factors, such as model uncertainties and external disturbances. To address this issue, we first leverage the deep Koopman operator, facilitated with a deep neural network, to establish an offline formulation of a global linearization model for a micro-nano free-floating space robot. Based on the estimated linearization model, we then employ the model predictive control method for online optimization control, achieving a significantly reduced computational burden. Additionally, a decay factor is integrated into the model predictive control optimization objective function to balance the precision of joint angles tracking with the suppression of base satellite attitude disturbance. To further address the modeling inaccuracies and external disturbances, we incorporate a disturbance observer based on a radial basis function neural network for online compensation within the model predictive control framework. This augmentation enhances tracking precision and robustness. Several groups of simulation results are carried out to demonstrate the effectiveness of the proposed method, showing its capability of energy consumption, disturbance rejection and enhanced robustness. These highlight the potential of the proposed method to improve the control performance of free-floating space robots, even in the absence of a precise dynamic model.