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Space robotics has been used extensively in complex space missions. Rigid-manipulator space robots may suffer from rigid-body collisions with targets. This collision is likely to cause damage to the space robot and the target. To overcome such a problem, a novel Continuum-Manipulator Space Robot (CMSR) for performing on-orbit servicing missions is proposed in this paper. Compared with rigid-manipulator space robots, CMSRs are able to perform compliant operations and avoid rigid-body collisions with a target. The CMSR consists of two kinds of flexible components, including solar arrays and continuum manipulators. The elastic vibrations of these flexible components disturb the position and attitude of CMSRs. The beating phenomenon introduced by the energy transfer among these flexible components can cause damage to solar arrays. The complicated dynamic coupling poses enormous challenges in dynamic modeling and vibration analysis. The dynamic model for CMSRs is derived and the mechanism of the beating phenomenon is analyzed in this paper. Simulation results show that an obvious beating phenomenon occurs and the amplitude of the solar arrays increases significantly when the natural frequencies of two kinds of flexible components are close. A method is provided to avoid the beating phenomenon.

The rapid development of space technology has made it increasingly important to use space robots for on-orbit services. Space crawling robots can perform extravehicular condition monitoring, spacecraft fault location and diagnosis, repair and maintenance by carrying different payloads and traversing the spacecraft surface, which has received wide attention from researchers. A prototype of space crawling robot has been designed in this work, which is a quadrupedal insect-like configuration with integrated bionic adhesion material on the bottom of the four feet, and can walk on the satellite surface in a gravity-free space environment. The design and implementation of the crawling robot control system is carried out based on Robot Operating System, including hardware system construction and software architecture design. The tripod gait was also designed to enable the robot to crawl more stably in space. At last, the basic capabilities of the designed space crawling robot are tested in the ground environment, and the results demonstrate the robot’s body control capability, omnidirectional walking capability, and obstacle crossing and avoidance capability.

With the rapid development of space technology and the increasing demand for space missions, the traditional spacecraft manufacturing, deployment and launch methods have been unable to meet existing needs. In-space assembly (ISA) technologies can effectively adapt to the assembly of large space structures, improve spacecraft performance, and reduce operating costs. In this paper, the development and technologies for ISA are reviewed. ISA is classified from multiple angles, and the research status of ISA is shown clearly through the visual mapping knowledge domain. Then the development status of autonomous robot assembly in the United States, Europe, Japan, Canada and China is reviewed. Furthermore, the key technologies of ISA are analyzed from three aspects: assembly structure design, robot technologies and integrated management technologies. ISA technologies are still facing major challenges and need to be further explored to promote future development. Finally, future development trends and potential applications of ISA are given, which show that ISA will play a vital role in human space exploration in the future.

Purpose of Review The purpose of this review is to highlight space autonomy advances across mission phases, capture the anticipated need for autonomy and associated rationale, assess state of the practice, and share thoughts for future advancements that could lead to a new frontier in space exploration. Recent Findings Over the past two decades, several autonomous functions and system-level capabilities have been demonstrated and used in spacecraft operations. In spite of that, spacecraft today remain largely reliant on ground in the loop to assess situations and plan next actions, using pre-scripted command sequences. Advances have been made across mission phases including spacecraft navigation; proximity operations; entry, descent, and landing; surface mobility and manipulation; and data handling. But past successful practices may not be sustainable for future exploration. The ability of ground operators to predict the outcome of their plans seriously diminishes when platforms physically interact with planetary bodies, as has been experienced in two decades of Mars surface operations. This results from uncertainties that arise due to limited knowledge, complex physical interaction with the environment, and limitations of associated models. Summary Robotics and autonomy are synergistic, wherein robotics provides flexibility, autonomy exercises it to more effectively and robustly explore unknown worlds. Such capabilities can be substantially advanced by leveraging the rapid growth in SmallSats, the relative accessibility of near-Earth objects, and the recent increase in launch opportunities.

For spacecraft swarms, the multi-agent localization algorithm must scale well with the number of spacecraft and adapt to time-varying communication and relative sensing networks. In this paper, we present a decentralized, scalable algorithm for swarm localization, called the Decentralized Pose Estimation (DPE) algorithm. The DPE considers both communication and relative sensing graphs and defines an observable local formation. Each spacecraft jointly localizes its local subset of spacecraft using direct and communicated measurements. Since the algorithm is local, the algorithm complexity does not grow with the number of spacecraft in the swarm. As part of the DPE, we present the Swarm Reference Frame Estimation (SRFE) algorithm, a distributed consensus algorithm to co-estimate a common Local-Vertical, Local-Horizontal (LVLH) frame. The DPE combined with the SRFE provides a scalable, fully-decentralized navigation solution that can be used for swarm control and motion planning. Numerical simulations and experiments using Caltech’s robotic spacecraft simulators are presented to validate the effectiveness and scalability of the DPE algorithm.

Using a space robot to capture a non-cooperative spacecraft with high-speed rotation is significantly challenging since any collision generated during capturing will have great impact on both. To reduce the risk in capturing operations, it is crucial to slow down the rotation velocity of the target before capturing. Hence, this paper studies a collision control strategy for using a robotic arm to detumble a non-cooperative spacecraft. The goal of this strategy is to maintain contact between the robot and the target and to apply continuous detumbling force on the target to slow down its rotational motion. To achieve that, first the mechanism analysis of the two balls for a central collision scenario is performed. Then an overdamping control method is proposed to avoid the separation of the balls after the central collision based on the overdamping property of the mass-spring-damper system, the effectiveness of which is validated theoretically. Finally, to use this overdamping control method in the detumbling missions of space robots, a position-based overdamping control strategy is introduced. In this strategy, the relative dynamic behavior between the robotic arm tip and the contact surface of the target during detumbling is approximated to that of a mass-spring-damper system. Owing to the proposed overdamping control method, the contact between the robot and the target can be maintained, and the space robot can apply continuous control torque to slow down the rotational velocity of the target. Numerical simulations are performed to demonstrate the validity of the proposed control strategy.

This paper presents a robust detumbling strategy for a spacecraft equipped with a robotic manipulator to detumble a non-cooperative target with unknown inertial parameters. Reported detumbling strategies in the literature have been formulated with the assumption of accurately known target inertial parameters (mass, inertia tensor, center of mass location) and without consideration of magnitude limits on the robotic spacecraft’s control inputs. In reality, it is unrealistic to assume accurate knowledge of the target’s inertial parameters and the robotic spacecraft will be subjected to limits on its control inputs. In this paper, a novel detumbling strategy is presented to detumble targets with unknown parameters utilizing only bounds on their inertial parameters. A desired detumbling trajectory is delineated using only bounds on the target’s inertial parameters and subjected to end-effector force/torque limits. Magnitude constraints on the robotic spacecraft are taken into account by modeling them with a hyperbolic tangent function, which results in a system that is non-affine in its control inputs. To facilitate the development of the detumbling controller, an augmented model of the robotic spacecraft is formulated. Using bounds on the target’s inertial parameters, robust adaptive control approach is utilized to design the detumbling controller with the backstepping technique to ensure successful detumbling of the unknown target attached to the end-effector and rejection of its momentum. Numerical simulations have demonstrated the effectiveness of the proposed method.

Future on-orbit servicing and assembly missions will require space robots capable of manoeuvring safely around their target. Several challenges arise when modelling, controlling and planning the motion of such systems, therefore, new methodologies are required. A safe approach towards the grasping point implies that the space robot must be able to use the additional degrees of freedom offered by the spacecraft base to aid the arm attain the target and avoid collisions and singularities. The controlled-floating space robot possesses this particularity of motion and will be utilised in this paper to design an optimal path generator. The path generator, based on a Genetic Algorithm, takes advantage of the dynamic coupling effect and the controlled motion of the spacecraft base to safely attain the target. It aims to minimise several objectives whilst satisfying multiple constraints. The key feature of this new path generator is that it requires only the Cartesian position of the point to grasp as an input, without prior knowledge a desired path. The results presented originate from the trajectory tracking using a nonlinear adaptive H ∞ controller for the motion of the arm and its base simultaneously.

Recently, with the rapid development of aerospace technology, an increasing number of spacecraft is being launched into space. Additionally, the demands for on-orbit servicing (OOS) missions are rapidly increasing. Space robotics is one of the most promising approaches for various OOS missions; thus, research on space robotics technologies for OOS has attracted increased attention from space agencies and universities worldwide. In this paper, we review the structures, ground verification, and on-orbit kinematics calibration technologies of space robotic systems for OOS. First, we systematically summarize the development of space robotic systems and OOS programs based on space robotics. Then, according to the structures and applications, these systems are divided into three categories: large space manipulators, humanoid space robots, and small space manipulators. According to the capture mechanisms adopted, the end-effectors are systematically analyzed. Furthermore, the ground verification facilities used to simulate a microgravity environment are summarized and compared. Additionally, the on-orbit kinematics calibration technologies are discussed and analyzed compared with the kinematics calibration technologies of industrial manipulators with regard to four aspects. Finally, the development trends of the structures, verification, and calibration technologies are discussed to extend this review work.

Target capture is a fundamental and essential task of space robots for on-orbit servicing in the future. Accordingly, it is important to study the method for space robot stabilization after impact during target capture. In this paper, the stabilization control problem of a combined spacecraft after multiple impacts during target capture is studied. A dual-integral sliding mode (DISM) control method based on the reconfiguration of the reaction wheels is proposed. The stability control of the combined spacecraft is achieved by controlling the reaction wheels of the space robot to absorb the angular momentum arising from the impact. First, given the structure of the gripper, the contact detection algorithm and contact dynamics model are established, and then multiple impacts are simulated during the target capturing operation. Second, an improved sliding mode control method is proposed to overcome the influence of multiple impacts, and the stability of the controller is confirmed by the Lyapunov method. Third, through an optimization method, the configuration of the reaction wheels of the space robot is reconstructed to avoid control torque saturation. The validity and availability are eventually verified by simulations and experiments. The results show that the proposed method can achieve the stability of the combined spacecraft after the target capture, and the algorithm is robust and has engineering applicability.

With the number of large-scale facilities, malfunctioning spacecraft, and debris expected to increase in space, on-orbit servicing, including assembly, monitoring, maintenance, refueling and deorbiting, has become a major concern in space missions. Space robots can efficiently cope with a large number of on-orbit servicing missions while avoiding the high risks and reducing costs of extravehicular activity. The challenges of space robots with multiple arms include the complex dynamics and the coupling between the floating base and the end-effector. To handle these problems, a dynamics model with topological structure is firstly established for a four-arm space robot based on the kinematic chain symbolic calculus system and Axis-Invariants, which have the benefits of iterative structure and can avoid complex derivation of traditional dynamics modeling methods. Then, an attitude stabilization strategy consisting of improved nonlinear model predictive control and a hybrid actuator is implemented to handle the disturbance generated by the manipulation of multiple robot arms. The hybrid actuator can provide accurate control torque while simultaneously avoiding the singularity and saturation of the control moment gyro and reaction wheel, respectively. Finally, a scenario of space debris recycling is used to demonstrate the effectiveness of the proposed modeling and control strategy for on-orbit servicing missions with multiarmed space robots.

Capture and removal of space debris are challenging in robotic on-orbit servicing activities. A large portion of space debris does not possess any graspable features, which makes the conventional grippers inapplicable. To handle such nongraspable objects, a space robotic capture system is presented. A dual-arm space robot simulator that has the advantages of miniaturization and scalability is designed for ground tests. Inspired by the robotic caging, we propose a novel capture method that uses a series of hollow-shaped end-effector pairs to cage the antipodal pairs of the nongraspable objects. To apply the caging-pair method steadily, space robots need exerting a squeezing action on objects, which can be characterized by the motion and force manipulation of two robotic arms in the assigned directions. Based on the velocity and force manipulability transmission ratios, a caging compatibility index is proposed to describe the capturing ability in this manner. Via the optimization of the desired caging compatibility index, an effective algorithm is proposed to plan the near-optimal joint configurations for the pregrasping cages. Finally, both simulation studies and experimental tests are conducted to evaluate the performance of the proposed capture method.

This paper presents a trajectory planning method for a dual-arm space robot that is free-floating and receives no actuation from the base spacecraft. The task is to capture a target by a mission arm and accomplish base manoeuvring with the coupling effects by a manoeuvring arm. Three manoeuvring cases for the base are discussed concerning attitude regulation, attitude tracking and position tracking. In all cases, an optimization method is applied to solve for the joint velocity of the arms, which ensures that the joint states of the mission arm obtain the desired states for capturing and control the motion of the base. Moreover, the collision avoidance of the manoeuvring arm with the base and mission arm is considered an inequality constraint. In particular, the joint velocity of the mission arm is represented by a new variable to remove the disturbance caused by the mission arm on the attitude of the base which makes it easier to complete the attitude manoeuvring case. Finally, numerical simulations are carried out by the planar and spatial dual-arm robots to validate the efficiency of the control strategy during both capturing and base manoeuvring.

Game-based competitive or cooperative robotics activities constitute an effective approach to exploit the child-robot interaction perspective. However, in most game-based robotics activities robots act autonomously to achieve the goal. In this work, we aim to promote the child-robot interaction aspect through a multiplayer game where one team of robots and humans collaborates to compete with another team of humans and cobots. We describe the design of an open space that will allow children to gain access, locally and remotely, and program robotic agents to play the traditional “Capture the Flag” game in a physical stadium-arena. Through this space, we intend to teach robotics, while programming human-robot interfaces, within a computer-supported game-based learning environment. We give insights on the initial design of such an open space and the educational benefits of its use in the comprehension of abstract computational and STEM concepts.

Designing A highly-reliable modular joint system for low speed and large inertia space manipulators has been one of the grand challenges in robotics research. It is too difficult for the conventional joints for satisfy the requirements of aerospace applications. To address this challenge, this paper details the hardware and control development for a highly-reliable modular joints system, intended for use in highly space manipulators.

The traditional trajectory planning methods of free-floating space robots have the dynamic singular problem and the difficulty of accurate modeling. Although learning-based approaches have achieved remarkable performance on such task, they mainly focus on single modular design such as the perception, planning, or control part. Optimization-based end-to-end method can well combine perception, planning and control, which not rely on parameters of the dynamic model and reduce the difficulty of manually adjusting modular controllers’ parameters. Therefore, we developed an end-to-end trajectory planning strategy based on optimization with multiple constraints. The whole strategy consists of several multi-layer neural networks and is optimized by a deep reinforcement learning algorithm based on maximum entropy. The results of visualization show that our strategy can capture the information of robotic arm from vision directly. Moreover, we evaluate the kinematic and dynamic features of the system and testify our strategy in anti-interference experiments. The performance of our strategy demonstrates the availability and robustness of the system.

Some problems on in-flight verification of the navigation, guidance and control systems for the information satellites and space robots are considered. Digital algorithms for reliable control of these spacecraft and obtained results are presented.

Visual terrain-relative navigation (VTRN) is a localization method based on registering a source image taken from a robotic vehicle against a georeferenced target image. With high-resolution imagery databases of Earth and other planets now available, VTRN offers accurate, drift-free navigation for air and space robots even in the absence of external positioning signals. Despite its potential for high accuracy, however, VTRN remains extremely fragile to common and predictable seasonal effects, such as lighting, vegetation changes, and snow cover. Engineered registration algorithms are mature and have provable geometric advantages but cannot accommodate the content changes caused by seasonal effects and have poor matching skill. Approaches based on deep learning can accommodate image content changes but produce opaque position estimates that either lack an interpretable uncertainty or require tedious human annotation. In this work, we address these issues with targeted use of deep learning within an image transform architecture, which converts seasonal imagery to a stable, invariant domain that can be used by conventional algorithms without modification. Our transform preserves the geometric structure and uncertainty estimates of legacy approaches and demonstrates superior performance under extreme seasonal changes while also being easy to train and highly generalizable. We show that classical registration methods perform exceptionally well for robotic visual navigation when stabilized with the proposed architecture and are able to consistently anticipate reliable imagery. Gross mismatches were nearly eliminated in challenging and realistic visual navigation tasks that also included topographic and perspective effects.

Aiming at addressing the problem that the joints are easily destroyed by the impact torque during the process of space robot on-orbit capturing a non-cooperative spacecraft, a reinforcement learning control algorithm combined with a compliant mechanism is proposed to achieve buffer compliance control. The compliant mechanism can not only absorb the impact energy through the deformation of its internal spring, but also limit the impact torque to a safe range by combining with the compliance control strategy. First of all, the dynamic models of the space robot and the target spacecraft before capture are obtained by using the Lagrange approach and Newton-Euler method. After that, based on the law of conservation of momentum, the constraints of kinematics and velocity, the integrated dynamic model of the post-capture hybrid system is derived. Considering the unstable hybrid system, a buffer compliance control based on reinforcement learning is proposed for the stable control. The associative search network is employed to approximate unknown nonlinear functions, an adaptive critic network is utilized to construct reinforcement signal to tune the associative search network. The numerical simulation shows that the proposed control scheme can reduce the impact torque acting on joints by 76.6% at the maximum and 58.7% at the minimum in the capturing operation phase. And in the stable control phase, the impact torque acting on the joints were limited within the safety threshold, which can avoid overload and damage of the joint actuators.

Over the past few decades a considerable number of studies have been made on impact dynamics. Zheng and Hemami discussed a mathematical model of a robot that collides with an environment (Zheng & Hemami, 1985). When a robot arm fixed on the ground collides with a hard environment, the transition from the free space to constrained space may bring instability in the control system. Therefore, the impact between robots and environments has been the subject of controversy. Asada and Ogawa analyzed the dynamics of a robot arm interacting with an environment using the inverse inertia matrices (Asada & Ogawa, 1987). In the early 90’s, the optimum approach velocity for force-controlled contact has been enthusiastically studied (Nagata et al., 1990, Kitagaki & Uchiyama, 1992). Volpe and Khosla proposed an impact control scheme for stable hard-on-hard contact of a robot arm with an environment (Volpe & Khosla, 1993). Mills and Lokhorst proposed a discontinuous control approach for the tasks that require robot arms to make a transition from non-contact motion to contact motion, and from contact motion to non-contact motion (Mills & Lokhorst, 1993). Walker proposed measures named the dynamic impact measure and the generalized impact measure to evaluate the effects of impact on robot arms (Walker, 1994). Mandal and Payandeh discussed a unified control strategy capable of achieving a stable contact against both hard and soft environment (Mandal & Payandeh, 1995). Tarn et al. proposed a sensor-referenced control method using positive acceleration feedback and switching control strategy for robot impact control (Tarn et al., 1996). Space robots does not have fixed bases, therefore, an impact with other free-floating objects may bring the space robots a catastrophe. In order to minimize the impulsive reaction force or attitude disturbance at the base of a space robot, strategies for colliding using reaction null-space have been proposed (Yoshida & Nenchev, 1995, Nenchev & Yoshida, 1998). Most of the researches have been made to overcome the problems introduced by impacts between robots and environments. Some researchers have tried to use the advantages of impacts. When a robot applies a force statically on an environment, the magnitude of force is limited by the maximum torque of the actuators. In order to exert a large force on the environment beyond the limitation, applying impulsive force has been studied by a few researchers. Uchiyama performed a nail task by a 3-DOF robotic manipulator (Uchiyama, 1975). Takase et al. developed a two-arm robotic manipulator named Robot Carpenter, and performed sawing a wooden plate and nailing (Takase, 1990). Izumi and Hitaka proposed to use a flexible link manipulator for nailing task, because the flexible link has an advantage in absorbing an impact (Izumi & Kitaka, 1993).

Communications and navigation are fundamental to robotic spacecraft exploration. NASA spacecraft communicates via radio links with antennas in the deep space network (DSN) located in California, Australia, and Spain. Measurements of range between the DSN and spacecraft are an important and sometimes critical contribution to navigation. For a given pair of uplink and downlink carriers, ranging must generally be accompanied by telemetering, in order to allow for efficient use of spacecraft and ground resources. Regenerative ranging, which is compatible with the simultaneous presence of telemetry, is more efficient in the use of link power than is the current standard (nonregenerative) ranging. This improved efficiency arises because regenerative ranging replaces the wideband filter found in a nonregenerative transponder's ranging channel with a narrowband loop that tracks the range code, so the signal-to-noise ratio in the transponder's ranging channel is large and there is essentially no noise modulated onto the downlink carrier. This paper offers a comparison of pseudonoise (PN) regenerative ranging versus the nonregenerative method of ranging. This paper also describes the implementation of PN regenerative ranging on the Iris transponder, which is a low-power, 0.5U size, DSN-compatible, software-defined radio based on various JPL flight transponder designs. Iris is baselined to be used on 7 out of 13 of the CubeSats flying as secondary payloads on the Space Launch System Exploration Mission-1 launch of the Orion spacecraft.

Space debris or uncontrolled satellites bring new and critical challenges for space robots to capture and remove them, especially when the targets are tumbling. In the face of these challenges, most existing research only focused on capturing a fixed point on the target. Distinguished from previous research, this paper attempts to investigate an autonomous tumbling target capturing method by approaching the “Dynamic Closest Point” (DCP), that is, the most suitable point on the target to be grasped and always closest to the end effector. First, an uncontrolled space object and a space robotic system are modeled, and the existence of the DCP is proved. For a practical malfunction spacecraft, the motion characteristics of the DCP and a fixed point are theoretically analyzed and compared as regards different motion types and rotation vectors. Furthermore, the desired trajectory is generated for the end effector of the space robot to approach the DCP autonomously, based on the position and velocity of the DCP estimated in real-time by hand-eye cameras. The joint velocities and angles are then resolved by combining the differential kinematics and movement constraints on the end effector. Finally, an Adams-Simulink co-simulation system is developed. Based on this, the proposed method is verified by single-arm and dual-arm capturing cases. Simulation results demonstrate that the capture time and movement ranges of the end effector are both greatly reduced with the DCP method. In contrast with traditional capturing methods, the efficiency of this proposed method is largely improved.

Robotic science missions in remote environments, such as deep ocean and outer space, can involve studying phenomena that cannot directly be observed using on-board sensors but must be deduced by combining measurements of correlated variables with domain knowledge. Traditionally, in such missions, robots passively gather data along prescribed paths, while inference, path planning, and other high level decision making is largely performed by a supervisory science team located at a different location, often at a great distance. However, communication constraints hinder these processes, and hence the rate of scientific progress. This paper presents an active perception approach that aims to reduce robots’ reliance on human supervision and improve science productivity by encoding scientists’ domain knowledge and decision making process on-board. We present a Bayesian network architecture to compactly model critical aspects of scientific knowledge while remaining robust to observation and modeling uncertainty. We then formulate path planning and sensor scheduling as an information gain maximization problem, and propose a sampling-based solution based on Monte Carlo tree search to plan informative sensing actions which exploit the knowledge encoded in the network. The computational complexity of our framework does not grow with the number of observations taken and allows long horizon planning in an anytime manner, making it highly applicable to field robotics with constrained computing. Simulation results show statistically significant performance improvements over baseline methods, and we validate the practicality of our approach through both hardware experiments and simulated experiments with field data gathered during the NASA Mojave Volatiles Prospector science expedition.

Large-aperture space telescope is the key equipment for studying the origin and evolution of the universe and various celestial bodies. Developing large-aperture space telescope is challenging and has become a priority in the field of optical engineering. Due to the mass and volume constraints of launch vehicles, it has to be designed and launched in modules and then assembled on-orbit by space robots. In this paper, we present a conceptual of 10-meter diameter modular space telescope together with robotic assembly strategy. To fulfill on-orbit assembly and maintenance of the space telescope, a novel assembly robot with a ring-shaped mobile base and a redundant stretchable manipulator is proposed. The time-optimal trajectory planning based on genetic algorithm is utilized to achieve efficient assembly. The preliminary ground experiment of assembling submirror modules of space telescope using the KUKA LWR iiwa-7 is carried to verify the feasibility of the proposed method, and the results show that the assembly task of telescope modules can be accomplished successfully with appropriate forces and torques.

Problems of nonlinear digital and pulse-width control for the spacecraft orientation in initial modes are considered – during their separation from a launcher rocket up to regular attitude stabilization in orbital reference frame. Developed methods, algorithms and the computer simulation results on the initial orientation modes of the small satellites and space robots in sun-synchronous orbit are presented.

Space robots have attracted increasing attention for performing, autonomously or telerobotically, on-orbit servicing missions such as repairing, refueling, and upgrading spacecraft; reusing space assets; and on-orbit assembly. The extension of robot application to space can release astronauts from risky, time-consuming, and expensive extravehicular activities [1]. However, in the microgravity environment, the floating base of a space robot will be disturbed by the robot's arm motion when it approaches or manipulates a target. The motion of the spacecraft base resulting from this disturbance will, conversely, affect the motion of end effectors (known as coupling dynamics), making control of space robots more complicated than that of fixed-base robots. In addition, such a disturbance of spacecraft attitude may result in a communication interruption between the spacecraft and the ground station or a failure of energy accumulation caused by disorientation of solar panels [2].

With the development of robotics in recent years, space robotic manipulators have become a research focus on space technologies. In the TianGong-2 (TG-2) spacelab mission, a human-robot collaborative on-orbit servicing experiment was planned as one of the three key tasks. The central component of this task is the TG-2 robotic manipulator, which is a multisensory in-vehicle space robot with multiple control modes, including a 6-DOF robotic arm, a five-fingered humanoid hand, hand-eye and global cameras, and on-orbit human-machine interfaces(space mouse and cyber glove). The design purpose of TG-2 robotic task is to complete various prototypical experiments under micro-g environment to validate key technologies of space robots and on-orbit human-robot collaboration and gain experience and experimental data about robotic on-orbit servicing by assisting or cooperating with human astronauts. A variable time-scale motion plan method, which could adjusts the trajectories of the robot to reduce or eliminate the collision force between the robot collide with the environment, is developed for safe human-robot collaboration. The five-fingered hand grasp control is based on an approach coined as “coordinated grasp control based object Cartesian stiffness” for the adaptation of external forces and robust grasp. To solve the kinematic mapping from cyber glove commands to five-fingered robotic hand, a fingertip-position-based method is proposed to acquire precise solutions. The TG-2 robotic manipulator was launched to space in Sep. 15, 2016. From Oct. 27 to Nov. 13, 2016, all the planned experiments, including dynamic parameter identification, grasping floating objects and prototypical on-orbit servicing, were carried out successfully under the supervision and assistance of the two astronauts, laying foundations for the future applications of space robots.

Self-sufficient, robotic spacecraft require estimates of their hardware health state in order to project future system state and plan actions toward achieving mission goals. In this paper, we report on integration of a Model-Based Fault Diagnosis (MBFD) model and reasoning engine into flight software leveraging the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, including test results against captured flight data using the ASTERIA system testbed. Our effort integrated the Model-based Off-Nominal State Identification and Detection (MONSID) model-based reasoning system, developed by Okean Solutions, into ASTERIA flight software using the F Prime software framework. The MONSID engine was supplied with a model of the Blue Canyon Technologies XACT attitude control system (ACS) and tested against flight data and seeded fault tests. While we were unable to conduct an on-board experiment due to the premature loss of ASTERIA, our effort proved the feasibility of on-board model-based fault management, demonstrating reliable and accurate diagnosis using captured data, and further supporting a closed-loop spacecraft autonomy demonstration including autonomous navigation in off-nominal conditions.

Space missions have required the development of specific embedded systems for spacecraft applications, making reuse of existing software difficult. JAXA's space robot operating system (SP-ROS) initiative tackles this problem in order to realize more intelligent robotic space missions. JAXA's SP-ROS initiative proposes an open-source software framework for robots used in outer space and will facilitate the development of space robotics through the ROS and cFS system (RACS). This paper introduces RACS and describes a planned demonstration in space. RACS provides two functionalities. The first one is ROS/cFE converter, which makes it possible to directly incorporate the code of a ground robot application into an environment that can be ported as a spacecraft application. The porting of existing robotic applications will aid in developing new applications using ROS's rich development environment. The second functionality of RACS is the ROS/cFE bridge, which allows native cFS and ROS programs to interact. This is aimed mainly at making ground robotics software testing easier. Another benefit would allow ROS's development tools (Rviz and Gazebo) and libraries (OpenCV and MoveIt), as well as packages developed by the roboticists anywhere in the world, to be directly incorporated in the testing. Provided the onboard computer supports cFS, it will be possible to implement these software packages into space robots. JAXA has made the open-source RACS module available to everybody. We currently propose to test the system in a space demonstration using Int-Ball2, a space drone in the International Space Station (ISS).

As the space environment is difficult to be recreated on the earth, it is essential to develop a software toolkit to validate the parameters designing for space robots. In this paper, a toolkit addressed for dynamic control rapid prototype simulation system of the space robot was presented. Based on the real-time control technology, the toolkit was consisted of real-time dynamic computing, redundant dual-arm control system, visual imaging and measurement and teleoperation. Specifically, the collision problem involved in the manipulator end effector and the target could be analyzed by contact dynamics models in the real-time dynamic computing module. Furthermore, a peg-in-hole (multi cores) assembly experiment involving the disassembly for the space electrical connectors was carried out, which was adopted to evaluate the simulation effect of toolkit. Our results showed that the connection between the space plug and socket with multi cores was well built up in the simulation environment. Moreover, the toolkit can be used to make simulations of on orbit operational missions by multiple of human-computer interaction, which is the key for the evaluation of control algorithm applied on the space robot.

This paper adds on to the on-going efforts to provide more autonomy to space robots and introduces the concept of programming by demonstration or imitation learning for trajectory planning of manipulators on free-floating spacecraft. A redundant 7-DoF robotic arm is mounted on small spacecraft dedicated for debris removal, on-orbit servicing and assembly, autonomous and rendezvous docking. The motion of robot (or manipulator) arm induces reaction forces on the spacecraft and hence its attitude changes prompting the Attitude Determination and Control System (ADCS) to take large corrective action. The method introduced here is capable of finding the trajectory that minimizes the attitudinal changes thereby reducing the load on ADCS. One of the critical elements in spacecraft trajectory planning and control is the power consumption. The approach introduced in this work carry out trajectory learning offline by collecting data from demonstrations and encoding it as a probabilistic distribution of trajectories. The learned trajectory distribution can be used for planning in previously unseen situations by conditioning the probabilistic distribution. Hence almost no power is required for computations after deployment. Sampling from a conditioned distribution provides several possible trajectories from the same start to goal state. To determine the trajectory that minimizes attitudinal changes, a cost term is defined and the trajectory which minimizes this cost is considered the optimal one.

Neutral buoyancy systems simulate the microgravity environment by taking advantage of buoyancy forces of water to offset the gravity of test bodies. Functional verification of space robots in neutral buoyancy system is of great importance for ground tests. The relative pose determination of a spacecraft plays an essential role in the on-orbit operation of space robots. In order to meet the requirement of on-orbit operation ground verification for space robots, this paper develops a vision-based system for determining the relative pose of cooperative spacecraft in neutral buoyancy environment. Cooperative markers and underwater binocular vision system are designed for the pose determination, and a cooperative spacecraft model is built. A detection and recognition method based on the topological characteristic is proposed for the cooperative marker. An underwater imaging model of binocular camera is established, and its refraction parameters are calibrated. The marker points are measured with an underwater binocular 3D measurement algorithm. Furthermore, the pose of cooperative spacecraft is determined using axisymmetric plane feature points. Additionally, the stable and reliable pose and velocity are obtained after the data are further processed with a Kalman filter. Finally, the experiments are carried out and the experimental results show that the proposed system can achieve a stable and reliable high-precision relative pose determination for cooperative spacecraft in neutral buoyancy environment.

The prerequisite for space robots on-orbit capturing and servicing is to inspect and track the attitude of the target satellite. However, the number of DOFs (degrees of freedom) of space robot is limited, which cannot satisfy the position and attitude tracking of space robot end and the zero disturbance of the satellite base attitude at the same time. The multi-task priority motion planning method of space robot is adopted, which can realize the attitude tracking of space robot end and the zero disturbance of the satellite base attitude, while the position tracking of space robot end can be optimized. The simulation experiment results show that the method is effective.

Planetary surface sampling manipulators are space robots that perform sampling tasks on the planet surface. They are usually mounted on a planetary lander or a planetary rover to perform multi-point sampling and other operations.

In 1981, the Shuttle Remote Manipulator System (SRMS), developed by Canada, was put into orbit by the space shuttle Columbia, becoming the world’s first on-orbit operating robot for space applications (Siciliano and Khatib in Handbook of robotics. Springer, New York (2007) [1]).

Each spacecraft has to undergo comprehensive and rigorous ground verification prior to launch, and space robots are no exception. There are two ways for the ground verification for general spacecraft: simulation and physical testing, and the latter is the most commonly adopted method. Physical test of spacecraft at assembly-level is generally easier to conduct with full coverage of test conditions, because the ground simulation environment in which the products actually work can be easily set up. However, due to the size and weight (including payload weight) of the space robot system, as well as the challenge of simulating the on-orbit microgravity (or low gravity) environment in which the space robot systems are supposed to work, system-level ground verification test for space robot systems is very difficult to carry out. So, system verification of space robots is more difficult than that of general space mechanisms.

After the motion planning for space robots, the planned trajectory tracking will be implemented by joint motion.

Space robots have appeared and developed along with mission requirements and has been continuously upgraded and iterated with the propulsion of related technologies. It is foreseeable that the future development of space robotics will be closely related to the tasks of manned spaceflight, deep space exploration, and on-orbit services. Driven by the mission demands, space robotics will integrate the latest achievements in the development of science and technology, and will be constantly improved in form, function, and performance to meet the needs of space missions.

For different types of space robots, motion planning has different meanings. Motion planning of space robots usually refers to the process of generating the desired motion trajectory in the robot joint space or Cartesian space according to the mission target.

Space robots involve different operating objects and operating environments while performing missions. For example, for on-orbit servicing robots, the operating objects are mostly cooperative targets with the preset visual markers and dedicated operation interfaces, and the operating environment is a spacecraft surface structured environment, while for planetary exploration robots, the operating objects are mostly noncooperative targets without visual markers or dedicated operation interfaces, and the environment features are unknown and unstructured. Space robot perception refers to the process in which the space robot obtains the information of the operating objects and the operating environments by analyzing raw data generated by various sensors onboard.

We research the problems of checking the accuracy of long-term stabilization of information satellites and space robots with an asymmetric structure in geostationary orbit.

Small space robots have the potential to revolutionise space exploration by facilitating the on-orbit assembly of infrastructure, in shorter time scales, at reduced costs. Their commercial appeal will be further improved if such a system is also capable of performing on-orbit servicing missions, in line with the current drive to limit space debris and prolong the lifetime of satellites already in orbit. Whilst there have been a limited number of successful demonstrations of technologies capable of these on-orbit operations, the systems remain large and bespoke. The recent surge in small satellite technologies is changing the economics of space and in the near future, downsizing a space robot might become be a viable option with a host of bene�ts. This industry wide shift means some of the technologies for use with a downsized space robot, such as power and communication subsystems, now exist. However, there are still dynamic and control issues that need to be overcome before a downsized space robot can be capable of undertaking useful missions. This paper �rst outlines these issues, before analyzing the effect of downsizing a system on its operational capability. Therefore presenting the smallest controllable system such that the benefi�ts of a small space robot can be achieved with current technologies. The sizing of the base spacecraft and manipulator are addressed here. The design presented consists of a 3 link, 6 degrees of freedom robotic manipulator mounted on a 12U form factor satellite. The feasibility of this 12U space robot was evaluated in simulation and the in-depth results presented here support the hypothesis that a small space robot is a viable solution for in-orbit operations. Keywords: Small Satellite; Space Robot; In-orbit Assembly and Servicing; In-orbit operations; Free-Flying; Free-Floating.

In this article, the basic design solutions of the nodal element for the assembly of a truss mounted on a spacecraft are proposed. Soldering is considered as an automatic assembly method. The node element implements thermal contact, mechanical docking without backlash, provides transmission lines of digital and analog (if necessary) signals, as well as the transmission of electricity through a 27V network. At the same time, geometric parameters of the docking interface make it possible to assemble the truss on the basis of these nodal elements using existing space robots. The strength, thermal and residual deformations analyses are provided.

The NASA InSight Mars lander is a robotic spacecraft which is investigating the interior structure of Mars through a series of seismological measurements and experiments. Much of the commanding of activities performed by the instruments was done using ‘blocks’ - reusable functions written in Virtual Machine Language stored onboard the spacecraft- and sequences (series of commands) that were created by teams to operate their instruments. It was vital that these blocks and sequences (collectively called command products) be thoroughly examined prior to onboard execution using a comprehensive test program to reduce risk to the spacecraft and instruments and ensure smooth operations on the surface of Mars. The Verification and Validation (V&V) process that was designed and implemented during the months leading up to InSight's launch and landing successfully uncovered a number of issues that could have caused operational delays or impacted hardware. The process also helped adapt ground tools to better model onboard activities, create operational principles to avoid unintended consequences during flight, and generate a reference database for command product use during operations. This allowed InSight to meet its surface operations goals in the desired timeframe. This paper describes the development, implementation and results of InSight's command product V&V process, its contribution to mission success, and challenges faced.

Over the last few decades, Space robots have found their applications in various in-orbit operations. The Canadarm2 and the European Robotic Arm (ERA), onboard the International Space Station (ISS), are exceptional examples of supervised robotic manipulators (RMs) used for station assembly and maintenance. However, in the case of in-space assembly of structures, like Large-Aperture Space Telescope (LAT) with an aperture larger than the Hubble Space Telescope (HST) and James Webb Space Telescope (JWST), missions are still in its infancy; this is heavily attributed to the limitations of current state-of-the-art Robotics, Automation and Autonomous Systems (RAAS) for the extreme space environment. To address this challenge, this paper introduces the modelling and control of a candidate robotic architecture, inspired by Canadarm2 and ERA, for in-situ assembly of LAT. The kinematic and dynamic models of a five degrees-of-freedom (DoF) End-Over-End Walking robot’s (E-Walker’s) first phase of motion is presented. A closed-loop feedback system validates the system’s accurate gait pattern. The simulation results presented show that a Proportional-Integral-Derivative (PID) controller is able to track the desired joint angles without exceeding the joint torque limits; this ensures precise motion along the desired trajectory for one full cycle comprising of Phase-1 and Phase-2 respectively. The gait pattern of the E-Walker for the next phases is also briefly discussed.

Space robotics is regarded as one of the most impressing approaches for space debris removal missions. Due to the residual momentum of debris, it is essential to stabilize the base rapidly after capture. This paper presents a novel control strategy for stabilization of a space robot in postcapture considering actuator failures and bounded torques. In the control strategy, the motion of the manipulator is not regarded as a disturbance to the base; in contrast, it is utilized to compensate for the limitation of the control torques by means of an inverse dynamical model of the system. Different scenarios where actuators are external mechanisms or momentum exchange devices have been carried out, and for actuator failures, both single- and two-actuator failures have been considered. Regarding to the performance of actuators, control torques are bounded. In cases that either single or two actuators have failed, the base can be stabilized kinematically when actuators are external mechanisms, but can only be stabilized dynamically when only momentum exchange devices are used. Finally, a space robot with a seven-degree-of-freedom manipulator in postcapture is studied to verify the validity and feasibility of the proposed control scheme. Simulation results show that the whole system can be stabilized rapidly. Keywords: Actuator failure, Attitude control, Bounded torque, Postcapture, Space robot

A method of constructing bilateral supervisory control over space robots, which ensures the robot’s system functions in the case of large transmission delays of control signals from the ground control center to the local space robot’s control system, is described. The conditions for the stability of manipulating a robot and a sufficiently high level of transparency are found. An original positionforce glove-like interface to control the robot’s manipulation is proposed, which ensures greater transparency of the kinesthetic interaction of the human hand with objects of the external environment than is the case with traditional interfaces in the form of a driving handle.

The trajectory and boundary of an orbiting satellite are fundamental information for on-orbit repairing and manipulation by space robots. This task, however, is challenging owing to the freely and rapidly motion of on-orbiting satellites, the quickly varying background and the sudden change in illumination conditions. Traditional segmentation usually relies on a large annotated dataset and needs to be pre-trained for each target, which exhausts much time in both training and testing due to the large number and resolution of the images. In this paper, we proposed a STSS (Saliency and Tracking based Semi-supervised Learning for Segmentation) algorithm that provides the segmentation binary mask of target satellites at 12 frames per second without requirement of annotated data. Our method, STSS, improves the segmentation performance by generating a saliency map based semi-supervised on-line learning approach within the initial bounding box estimated by tracking. Experiment is evaluated on our generated dataset, which contains various challenges including variation in target, background and illumination condition.

Formation control is a potential advanced technology for aircrafts, spacecrafts and space robots. This paper, for the first time, studies several methods of passive and semi-active Remote Center Compliance (RCC) in order to examine their effects on formation control of a group of Wheeled Mobile Robots (WMRs) for object manipulation during space/terrestrial explorations. To this end, first, the dynamics model of the constrained non-holonomic robots, object and RCC system have been derived precisely. A leader-follower control strategy is then utilized for trajectory tracking of the desired path by the cooperative robots. Finally, the passive and semi active RCC are optimized to make the formation robust in the presence of significant disturbances. The results obtained reveal that the semi-active RCC system, combined with a PID controller, reduces the effect of the disturbances experienced as compared to the other passive RCC modules.