Free-floating Space Robot Research Articles

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.

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.

Dynamic Modeling and Improved Nonlinear Model Predictive Control of a Free-Floating Dual-Arm Space Robot

With the increasing demand for space missions, space robots have become the focus of research and attention. As a typical representative, the free-floating dual-arm space robot has the characteristics of multiple degrees of freedom, a floating base, and dynamic coupling between the manipulator and the base, so its modeling and control are very challenging. To address these challenges, a novel dynamic modeling and control method is proposed for a free-floating dual-arm space robot. First, an explicit dynamic model of a free-floating dual-arm space robot is established based on the explicit canonical multi-rigid-body dynamic modeling theory and combined with the concept of a dynamic equivalent manipulator. The establishment process of this model is not only simple and canonical to avoid the definition and calculation of many intermediate variables, but the symbolic result expression of the model also has the characteristics of iteration, which is convenient for computer automatic modeling. Next, aiming at addressing the problem of trajectory tracking and the base attitude stability of a free-floating dual-arm space robot with parameter perturbation and external disturbance, an improved nonlinear model predictive control method introducing the idea of sliding mode variable structure is proposed. Theoretical analysis shows that the proposed controller has better robustness than the traditional nonlinear model predictive controller. Then, an in-orbit service task is designed to verify the effectiveness of the proposed dynamic modeling and control strategy of the free-floating dual-arm space robot. Finally, the dynamic modeling and control methods proposed are discussed and summarized. The proposed methods can not only realize the tracking of the desired trajectory of the arms of the free-floating space robot, but can also realize the stable control of the base of the free-floating space robot. This paper provides new insights into the difficult problems regarding the dynamics and control of free-floating dual-arm space robots.

Parameters identification and trajectory optimization of free-floating space robots

There is a strong dynamic coupling between the base of free-floating space robot and the space manipulator. In order to reduce the interference of the movement of the space manipulator on the robot's base, the trajectory of the space manipulator needs to be optimized. In this paper, the joint path of space manipulators is optimized by using the pseudo-spectral method to reduce the impact of the arm movement on the base. For space robots, parameters identification is the premise of trajectory planning. A parameters identification method is proposed, which only needs to measure the base's angular speed. Numerical simulation results verify the validity of the proposed method. The attitude angle of floating base returns to the initial state after maneuvers of space manipulators.

Anti-deadzone adaptive fuzzy dynamic surface control for planar space robot with elastic base and flexible links

In order to combat the impact of the dead zone and reduce vibration of the space robot's elastic base and flexible links, the trajectory tracking and vibration suppression of a multi-flexible-link free-floating space robot system are addressed. First, the elastic connection between the base and the link is considered as a linear spring. Then the assumed mode approach is used to derive the dynamic model of the flexible system. Secondly, a slow subsystem characterizing the rigid motion and a fast subsystem relating to vibration of the elastic base and multiple flexible links are generated utilizing two-time scale hypotheses of singular perturbation. For the slow subsystem with a dead zone in joint input torque, a dynamic surface control method with adaptive fuzzy approximator is designed. Dynamic surface control scheme is adopted to avoid calculation expansion and to simplify calculation. The fuzzy logic function is applied to approximate uncertain terms of the dynamic equation including the dead zone errors. For the fast subsystem, an optimal linear quadratic regulator controller is used to suppress the vibration of the multiple flexible links and elastic base, ensuring the stability and tracking accuracy of the system. Lastly, the simulation results verify the effectiveness of the proposed control strategy.

Trajectory planning of a dual-arm space robot for target capturing with minimizing base disturbance

During the on-orbit capture task of the free-floating space robot, its operating space degenerates. The dynamic coupling and dynamic singularity also affect the task operation. In this paper, a general collision-free trajectory planning method to minimize base disturbance is proposed for a free-floating dual-arm space robot. This method can realize smooth joint trajectory planning while avoiding singularity and realizing self-collision avoidance. The singularity can be effectively avoided by transforming the trajectory planning problem into a nonlinear optimization problem. The optimization function is composed of base disturbance penalty function, end effector error function and collision repulsion potential field function, which can be used to solve the optimal joint trajectory parameters. Futhermore, self-collision avoidance is achieved by combining the bacterial foraging optimization algorithm(BFOA) with the geometric vector collision-avoidance method based on artificial potential field to simplify the calculation complexity. Finally, simulations verify the effectiveness of the proposed planning framework.

Reinforcement learning with prior policy guidance for motion planning of dual-arm free-floating space robot

Reinforcement learning methods as a promising technique have achieved superior results in the motion planning of free-floating space robots. However, due to the increase in planning dimension and the intensification of system dynamics coupling, the motion planning of dual-arm free-floating space robots remains an open challenge. In particular, the current study cannot handle the task of capturing a non-cooperative object due to the lack of the pose constraint of the end-effectors. To address the problem, we propose a novel algorithm, EfficientLPT, to facilitate RL-based methods to improve planning accuracy efficiently. Our core contributions are constructing a mixed policy with prior knowledge guidance and introducing ‖⋅‖∞ to build a more reasonable reward function. Furthermore, our method successfully captures a rotating object with different spinning speeds.

Adaptive neural network vibration suppression control of flexible joints space manipulator based on H∞ theory

Considering the control problems caused by uncertainties such as inaccurate modeling, external disturbance and joint flexibility, a neural network control method based on H∞ is proposed. By establishing the dynamic model of the free-floating space robot with flexible joints, according to its dynamic characteristics, it is split into a slow subsystem model representing the rigid characteristics and a fast subsystem model representing the flexible characteristics. Based on the H∞ robust control theory, a robust controller based on neural network is designed to realize the decoupling control of the rigid dynamic model, The designed weight adaptive learning rate can ensure the online and real-time adjustment of parameters. Based on Lyapunov theory, it is proved that the designed controller can ensure that the L2 gain of the system is less than the given index. A feedback controller based on velocity differential is designed to compensate the angle error caused by joint flexibility. The experimental simulation results verify that the proposed control method is effective and has good engineering application value.

Risk Assessment Model-Guided Configuration Optimization for Free-Floating Space Robot Performing Contact Task

The use of free-floating space robots for contact tasks is very promising in space exploration. However, severe damage or obvious disturbance may occur if inappropriate operation is implemented. In this paper, a novel risk assessment method is first proposed to give a clear description of the risk state before contact happens and provide guidance for configuration optimization to reduce risk on contact tasks. Firstly, the dynamics model of a free-floating space robot is given. On this basis, two important risk assessment indicators, the maximum contact force and the base attitude disturbance caused by contact, are derived. By integrating the risk assessment indicators, a novel risk assessment model is proposed for a free-floating space robot performing a contact task. It is a multidimensional and extensible risk assessment space which could give a clear description of the risk state before contact happens. Thereafter, considering the results given by the risk assessment model, the configuration optimization for a free-floating space robot is implemented based on the design of optimization factor in null space. Finally, numerical simulation for a 7-degree-of-freedom free-floating space robot performing a contact task is carried out, and the simulation results verify the effectiveness of the proposed method.

Coordinate-Free Jacobian Motion Planning: A 3-D Space Robot

We address the motion planning problem for a robotic system whose configuration manifold contains a group of rotations. Our approach is applied to a free-floating space robot composed of a three-dimensional base (a spacecraft) and an anthropomorphic onboard manipulator. The robot is actuated by the torques exerted at the joints of the onboard manipulator. A coordinate-free representation of rotations is utilized. The Lagrangian formalism is employed in order to derive a dynamics model of the robot that takes the form of a control system defined on the group of rotations and the joint space of the onboard manipulator. Using the conservation of angular momentum of the robot, a Jacobian motion planning algorithm is designed relying on the Endogenous Configuration Space Approach. The performance of the algorithm is verified by computer simulations.

Optimal Trajectory Planning for Minimizing Base Disturbance of a Redundant Space Robot with IQPSO

With the development of aerospace technology, the practical application of a free-floating redundant space robot has become more and more popular. The problem of minimizing base disturbance has been paid attention among academic researchers. If the space robot moves, it would have an impact on the pose of a base. The interference on a base should be reduced, which was caused by the movements of the space robot. In the paper, the simplified model of a redundant space robot has been described, which consists of a base and a 7-joint manipulator. Using the nonholonomic redundancy features, the pose of the base has been optimized planning. First, a set of kinematic equations of the redundant space robot was founded. Second, the 5-order polynomial function could be used for the parametric 7 joints. Third, on the basis of the pose requirements, a fitness function was defined. At last, the proposed improved quantum particle swarm optimization (IQPSO) algorithm was presented. The proposed IQPSO algorithm not only searched the optimal value easily but also had a good robust performance. The advantages could be shown through the numerical experiments, compared with the quantum-behaved particle swarm optimization (QPSO) algorithm, particle swarm optimization (PSO) algorithm, and simulated annealing particle swarm (SAPSO) algorithm. Then, the proposed IQPSO algorithm was used to optimize the fitness function of trajectory planning. By the simulation results, it could be confirmed that the proposed IQPSO algorithm searched the global optimal solution not only easily but also smoothly, compared with the QPSO, PSO, and SAPSO algorithms. The proposed approach was suitable for planning an optimal trajectory.

Error model-oriented vibration suppression control of free-floating space robot with flexible joints based on adaptive neural network

At the same time, considering the uncertain factors such as load variation, external interference and joint flexibility in engineering practice, a robust control method based on adaptive neural network is proposed. The dynamic model of free-floating space robot is established, and the error model caused by uncertain factors is deduced. Different from the traditional compensation algorithm that ignores the error model, a compensation controller based on Radial basis function neural network (RBFNN) is designed to approximate the error model. The approximation error is eliminated by robust controller to improve the control accuracy. In order to make full use of the nonlinear approximation ability of neural network, the error model is decomposed into four parts according to the input characteristics, and the neural network compensator is designed for separate and overall compensation, which further improves the control accuracy and robustness. The adaptive learning rates of network weights are designed to ensure online real-time adjustment without offline learning stage. A flexible compensator based on torque and a controller based on moment difference feedback controller (MDFC) are designed to suppress elastic vibration. Simulation and experimental studies show that the proposed strategy can have good compensation performance and robustness, and can better suppress elastic vibration, which proves the effectiveness and superiority of the proposed scheme.

Impedance Control of Space Robot On-Orbit Insertion and Extraction Based on Prescribed Performance Method

Aiming at the force position control problem of the on-orbit insertion and extraction operation of the free-floating space robot, the system dynamics model is established. According to the interaction between the end of manipulator and the environment, the second-order impedance model is established. In order to improves the calculation efficiency, the above models are reconstructed to avoid the use of acceleration signal by introducing filtering operation. This is also conducive to the application of robot actual control. Then, an estimator requiring only the system inertia matrix is designed to compensate the modeling uncertainty, external bounded disturbance and impact effect in the process of inserting and extracting. Its structure is simple and reliable. Only one control parameter needs to be adjusted, which greatly reduces the amount of calculation. Considering that the on-orbit operation of insertion and extraction is a kind of precision operation, its control system needs to have a high-quality control performance. By introducing the prescribed performance method, the tracking error is constrained within the given range and to ensure the transient performance and steady-state performance of the control system is ensured. Finally, three simulation conditions are designed, and the results are presented to verify that the proposed algorithm has a faster convergence speed compared with traditional sliding mode controller. It can achieve vertically inserting and accurate force tracking of the manipulator end.

Trajectory Tracking for a Dual-Arm Free-Floating Space Robot With a Class of General Nonsingular Predefined-Time Terminal Sliding Mode

This paper addresses trajectory planning and control for a dual-arm free-floating space robot (FFSR) based on predefinedtime stability. Firstly, a class of general nonsingular terminal sliding mode control strategy is proposed to achieve global predefined-time stability by switching a control parameter in a form of function. Then, a high-precision trajectory planning method is proposed for a FFSR using the proposed predefined-time stability theorem, which can make the end-effector and the base reach the desired pose within a prespecified time, and reduce the adverse effect on planning accuracy resulted from the singularity avoidance algorithm and the obstacle avoidance one. Subsequently, a trajectory tracking control strategy is proposed for a FFSR employing the proposed general nonsingular predefined-time terminal sliding mode, and the tracking errors can converge within a predefined time to an arbitrarily small neighborhood of zero in the presence of persistent disturbances. The proposed trajectory planning method has the advantage of pose feedback, so can be combined with the trajectory tracking controller in the control process to further enhance the control performance for the FFSR. Simulation results validate the effectiveness of the proposed methodologies.

Trajectory Planning of Free-Floating Space Robot Based on Dual-Mode Switching

Trajectory Planning of Free-Floating Space Robot Based on Dual-Mode Switching

Collision-Free Trajectory Planning for a 6-DoF Free-Floating Space Robot via Hierarchical Decoupling Optimization

Collision-free trajectory planning is a critical technique for space robot mission. In this letter, we developed a model-free Hierarchical Decoupling Optimization (HDO) algorithm to realize 6D-pose multi-target trajectory planning for the free-floating space robot. In order to reduce the complexity of exploration, the whole system consists of two layers: the high-level policy completes the collision-free trajectory planning of the end-effector’s pose; the low-level policy divides the task of reaching arbitrary pose into two decoupling sub-tasks (position and orientation) within a large target space. By introducing the Hindsight Experience Replay (HER), we successfully trained two agents based on multi-goal reinforcement learning. We proposed an Event-based Alternating Optimization (EAO) to stabilize the training and efficiently approximate the optimal policy. Theoretical analysis shows EAO can guarantee the learning stability and reachability of the equilibrium point. The simulation results illustrate that the proposed algorithm achieves high environmental adaptability and anti-disturbance capacity. Furthermore, we demonstrated our proposed method in a practical space mission by applying it to capture a target satellite. Qualitative results (videos) are available at 1.

Trajectory planning and base attitude restoration of dual-arm free-floating space robot by enhanced bidirectional approach

When free-floating space robots perform space tasks, the satellite base attitude is disturbed by the dynamic coupling. The disturbance of the base orientation may affect the communication between the space robot and the control center on earth. In this paper, the enhanced bidirectional approach is proposed to plan the manipulator trajectory and eliminate the final base attitude variation. A novel acceleration level state equation for the nonholonomic problem is proposed, and a new intermediate variable-based Lyapunov function is derived and solved for smooth joint trajectory and restorable base trajectories. In the method, the state equation is first proposed for dual-arm robots with and without end constraints, and the system stability is analyzed to obtain the system input. The input modification further increases the system stability and simplifies the calculation complexity. Simulations are carried out in the end, and the proposed method is validated in minimizing final base attitude change and trajectory smoothness. Moreover, the minute internal force during the coordinated operation and the considerable computing efficiency increases the feasibility of the method during space tasks.

Configuration Optimization for Free-Floating Space Robot Capturing Tumbling Target

The maximum contact force is one of the most important indicators for contact problems. In this paper, the configuration optimization is conducted to reduce the maximum contact force for a free-floating space robot capturing tumbling target. First, the dynamics model of a free-floating space robot is given, with which the inertial properties perceived at the end-effector can be derived. Combing the inertial properties of the contact bodies, a novel concept of integrated effective mass is proposed. It tries to transform the complex contact process into the energy change of a virtual single body with integrated effective mass. On this basis, a more general continuous contact model is established, which is also suitable for non-central collisions between space robot and the tumbling target. Thereafter, the maximum contact force is derived as an important indicator for the null-space optimization method to reduce the maximum contact force. Finally, numerical simulations with a 3-degree-of-freedom free-floating space robot and a 7-degree-of-freedom free-floating space robot, as the research objects, are carried out respectively and the results show the effectiveness of the method proposed.

Research on QPSO algorithm for trajectory planning of FFSR general kinematics modeling

Aiming at the optimal trajectory planning problem faced by free floating space robot (FFSR) in capturing non cooperative target (NCT) with unknown dynamic parameters, firstly, based on the unique intrinsic characteristics of FFSR in microgravity environment, a general FFSR kinematic model based on generalized velocity variables and an NCT dynamic model based on quaternion method are established. Secondly, the optimal criterion of FFSR trajectory planning and the parametric modeling method of FFSR manipulator joint trajectory based on sinusoidal function are studied; Finally, a QPSO algorithm for FFSR trajectory planning based on the optimal comprehensive index is proposed

Nonlinear Model Predictive Control of Rotation Floating Space Robots for Autonomous Active Debris Removal

Active Debris removal using robotic manipulators onboard satellites is a promising way of cleaning up the space junk. However, complexities and non-linearities associated with the control of such coupled space-based systems present difficulties in their feasible implementation. Lack of a fixed base arises serious problems in controlling the space manipulators for precision tasks like capture of an orbiting space debris. This paper presents systematic modelling and control approaches for Rotation floating space robots in order to draw a comparison between them while tracking a moving target representing autonomous debris capture. We propose a Nonlinear Model Predictive Controller (NMPC) for the space robot in order to design an optimal path that the end-effector can follow while being controlled to capture the target. To the best of the knowledge of the authors, such a controller has not been tested for a Rotation floating space robot before. Further, the current work implements and reviews one of the most commonly used Transpose Jacobian Cartesian (TJC) controller for Rotation floating space robots through the use of Generalized Jacobian Matrix (GJM). The results provide sufficient evidence of the superior performance of the nonlinear model predictive controller over the TJC controller. Finally, the current work also implements the same nonlinear model predictive controller on a more popular state of the art Free floating space robot and compares it with the Rotation floating space robot.