Aggressive autonomous flight through narrow gaps presents a critical challenge in drone racing. As flapping-wing aerial vehicles (FWAVs) evolving toward autonomous navigation, avian-inspired FWAVs are significantly hindered by their single-modal flight dynamics and nonlinear underactuated characteristics, leading to the largely unexplored area of narrow gap traversal. To address this gap, this article introducesSparrowHawk, a compact autonomous flapping-wing system optimized for aerodynamic efficiency and structural rigidity. Its design enables a favorable payload-to-weight ratio, accommodating onboard sensing for external-positioning-free localization and maneuverable forward flight. By leveraging the cycle-averaged method for modeling, the system is simplified to a nonlinear time-invariant model, with kinematic and dynamic equations derived in a unified state-space formulation. For robust real-time gate detection during flight, an adaptive Hough transform-based visual algorithm is proposed, yielding pixel-space geometric parameters of gaps without any prior knowledge. The servo control framework employs a closed-loop dual-loop strategy, integrating a TECS-based altitude controller with a cascaded PID attitude controller to ensure precise position and orientation control during autonomous gap traversal. Indoor and outdoor flight experiments demonstrate thatSparrowHawkexecutes tight-radius banked turns and altitude control with a mean error of 0.345 m. The robot successfully traverses an 80 cm-diameter circular gap at speeds up to 5.6 m/s with a 60 cm wingspan, signifying the first achievement for FWAVs. Through multiple repeated trials, it achieved success rates of 80% under normal lighting and 60% under low-light conditions, significantly outperforming a human pilot, the conventional unmodified Hough circle detector, and the deep learning–based YOLOv11 algorithm. This work advances perception-driven control methodologies for FWAVs, paving the way for agile autonomous navigation in confined environments.

Most birds in nature rely on jumping for takeoff. Flapping-Wing Robots can flap and fly like birds but require an operator to take off, which are unable to generate sufficient lift to maintain flight at a low airspeed and must accelerate to take-off speed in a short time. It poses a challenge for the design of the jumping mechanism. This study is inspired by the jump-takeoff of birds and designs a simple and lightweight jumping leg, which is capable of storing and releasing energy with only one degree of freedom. In addition, a prototype was developed and tested, with a wingspan of 2 meters and a mass of 1.6 kilograms, accelerating to 4 m/s in 52 ms by jumping, achieving the jumping take-off from the ground.

Large flapping-wing aerial vehicles (FWAVs) face dual challenges in aerodynamic and structural design, with long-standing technical bottlenecks, particularly in roll maneuvers. In this study, by reverse-engineering the biomechanical mechanisms of raptor flight, we propose a bio-inspired wing-shoulder torsional mechanism and successfully developed an eagle-inspired flapping-wing aerial vehicle with a wingspan of 1.87m and a takeoff weight of 1,260g. A nonlinear explicit dynamics-lattice Boltzmann fluid-structure interaction (FSI) numerical model was innovatively established, comprehensively revealing the interaction mechanism between unsteady flapping flow fields and flexible wing deformations. Numerical simulations demonstrate that at a cruising speed of 8 m/s, the proposed mechanism generates a high-purity roll torque of 3.3 N·m (with a residual yaw torque of 0.2 N·m, torque purity ratio 16.5:1), while lift and thrust losses are below 1.5%. Flight experiments validate the exceptional performance of this mechanism in 3D maneuvers: a 360° barrel roll is completed in 2.6 seconds (average roll rate 136°/s). This study provides a theoretical framework and technological prototype for next-generation bio-inspired aerial vehicles that integrate efficient cruising with high maneuverability, marking the first instance where FWAVs surpass traditional aircraft in specific 3D maneuverability metrics.

A cable-driven segmented manipulator (CDSM) has considerable potential in narrow space operations because it has a slender and light body with flexible mobility. However, the existing CDSM segment driving mechanisms are coupled to each other. The driving distance of the rear segment cable is superimposed with that of the front segment cable, which renders the cables’ drive distance inconsistent. Moreover, the system kinematics, dynamics, and control become extremely complex. In this article, a novel decoupling driving mechanism is proposed to solve the coupling problem, simplifying the modeling and control of the CDSM. The routing of the driving cable is designed based on the characteristics of the symmetrical offset (i.e., the same magnitude but opposite in direction) of the cable length applicable to joints with one and two degrees of freedom. By modifying the direction of the driving cable in the middle of the proximal segment, the driving cable length of the distal segment is unaffected by the change of the angle of the front segment. Moreover, to increase the drive stroke, a multiturn winding mechanism is designed, reducing the volume and mass of the driving box. Accordingly, an improved forward and backward reaching inverse kinematics is proposed for CDSM based on virtual joints. Compared with the Jacobian pseudo-inverse method, the computational efficiency is improved. Finally, the proposed mechanisms and methods are verified via a CDSM prototype. The results indicate that the proposed manipulator compared with typical manipulators has larger movement range, higher end velocity, and guaranteed accuracy due to the proposed decoupled driving and fast kinematics resolution.

In recent years, there has been a growing demand for robotic manipulators to perform tasks in various unstructured environments and situations requiring precision and force control. However, traditional robotic arms have limitations in fully leveraging their advantages in such scenarios. To address this demand, we have designed a cable-driven serpentine manipulator (CDSM) that combines force and precision motion control. This control method allows for precise manipulation of forces and torques at the end-effector, particularly in applications like electric vehicle charging and narrow-space exploration. It also enables independent control in multiple configurations. We achieve force-position hybrid control in task space, ensuring accurate control of end-effector force while achieving precise position control in other directions. Additionally, we implement joint angle closed-loop control in joint space to reduce the impact of cable elasticity deformation and friction on joint motion accuracy. Finally, servo control is applied at the lowest motor level. This paper investigates the modeling, sensing, and control of CDSM within a unified framework of hybrid motion/force control. Through experiments and simulations, we demonstrate the high accuracy and practicality of this control method in various scenarios.

In this work, we achieved a self-takeoff of an eagle-scale flapping-wing robot for the first time. Inspired by the takeoff process of Ospreys, we propose a bio-inspired takeoff strategy, then discuss the dynamic model and the requirements for self-takeoff. Based on the requirements of flight strategy, we designed a system with two parts, including a flapping-wing aircraft with a wingspan of 1.8m and a take-off weight of 870g, and an auxiliary platform with an initial pitch angle adjustment function. In order to explore the differences in the take-off process under different conditions, we conduct the flight experiments under different time-averaged thrust-to-weight ratios (0.745-0.876) and launch angles (45°-90°). The results of flight experiments confirmed the theoretical analysis that the flapping-wing robot can achieve self-takeoff with no potential energy cost and maintain high maneuverability (The video shows a rapid climb immediately after takeoff) even when the time-averaged thrust-to-weight ratio is smaller than 1. This is significantly different from conventional rotary-wing and vertical take-off and landing (VTOL) UAVs. This work solves the challenge of self-takeoff for large-scale flapping-wing robots using a designable method and demonstrates the superior performance potential of flapping-wing robots compared to conventional UAVs.

In this paper, we present a spherical wheel-legged mobile robot, aiming to meet the demands of adaptability to complex terrains and high maneuverability. It consists of a spherical main body and five-bar linkage parallel wheel-legged mechanisms. It can switch between legged and spherical modes by extending and retracting its legs according to the demands of the actual environment, thereby enhancing the overall mobility of the robot. By designing the Linear Quadratic Regulator (LQR) controller, we achieve the impact-resistant leg balancing motion and autonomous pitch adjustment for the robot on inclined surfaces in the legged configuration. For the rolling control in the spherical configuration, a hierarchical sliding mode control method and Proportional-Integral-Derivative controller (PID) are employed to control the rolling and turning of the robot. We verify the robustness of the robot in wheel-legged configuration against disturbances and the stability of its motion in spherical configuration.

Large-scale flapping wing robots (FWRs) with airborne vision have important applications in visual navigation, aerial surveying, fire warning and power-line inspection. However, airborne vision and its videos suffer from strong jitters due to periodic wing flapping, which lowers the success rate of detection and measurement precision. In this paper, a robust digital video stabilization (DVS) method based on periodic jitters is proposed to provide continuous stable monitoring video without pan-tilt camera assistance. First, the periodic motion model of the FWR is established for video jitter analysis. Second, jitter frequencies in different flight states are estimated by continuous jitter acceleration. Then, feature trajectories generated from the video are adjusted adaptively for jitter frequency consistency and smoothed individually by the sampling-interpolation-averaging strategy, including the short trajectories. The stabilized video is generated by guidance from the original and smoothed trajectories. Finally, the proposed method is tested in outdoor flights with a 2.2-meter wingspan FWR and is found to outperform traditional, commercial, and deep learning DVS methods in terms of stability and robustness in various scenes and flight states.

The cable-driven redundant manipulator (CDRM) possesses remarkable flexibility and holds substantial potential for application in constrained environments. To ensure both the smooth movement of the end-effector during delicate operations and the safety of interactions with the surrounding environment, real-time sensing of forces acting on both the end and links is imperative. Current in situ sensor-based methods face limitations in their applicability to CDRMs due to size and load capacity constraints. Moreover, these methods fall short in measuring contact force and its location along the entire arm. In this article, we introduce an ex situ sensing approach for capturing the six-dimensional (6-D) force at the end and the contact force on the linkages of a CDRM. First, a multispace recursive dynamic model of the CDRM is established using the Newton–Euler method. This model establishes mapping relationships among cable tensions, joint torques, and operational forces at the end-effector. Then, a simplified dynamic model for the recursive subsystem is derived based on joint motion transmission relationships and recursive equations. This model decouples the dynamic equations and provides a versatile force-sensing model. It enables the realization of 6-D force/torque sensing at the end-effector, as well as the determination of the magnitude and location of external forces acting on the links. Finally, compliant controllers are designed based on different external force-sensing methods to cater to diverse operational requirements. Experimental validation of the proposed methods is conducted on a CDRM prototype. The results demonstrate that the accuracy of end-effector force sensing exceeds 95%, torque sensing surpasses 90%, and the positioning error of the link's contact force sensing is less than 20 mm. Furthermore, the compliance controllers exhibit excellent smoothness in tasks involving human–robot interaction.

This paper investigates one of the most challenging tasks in dynamic manipulation-catching large-momentum moving objects. Beyond the realm of quasi-static manipulation, dealing with highly dynamic objects can significantly improve the robot's capability of interacting with its surrounding environment. Yet, the inevitable motion mismatch between the fast moving object and the approaching robot will result in large impulsive forces, which lead to the unstable contacts and irreversible damage to both the object and the robot. To address the above problems, we propose an online optimization framework to: 1) estimate and predict the linear and angular motion of the object; 2) search and select the optimal contact locations across every surface of the object to mitigate impact through sequential quadratic programming (SQP); 3) simultaneously optimize the end-effector motion, stiffness, and contact force for both robots using multi-mode trajectory optimization (MMTO); and 4) realise the impact-aware catching motion on the compliant robotic system based on indirect force controller. We validate the impulse distribution, contact selection, and impactaware MMTO algorithms in simulation and demonstrate the benefits of the proposed framework in real-world experiments including catching large-momentum moving objects with welldefined motion, constrained motion and free-flying motion.

Dynamic movement primitives (DMPs) have been widely applied in robot motion planning and control. However, in some special cases, original discrete DMP fails to generalize proper trajectories. Moreover, it is difficult to produce trajectories on the curved surface. To solve the above problems, a modified DMP method is proposed for robot control by adding the scaling factor and force coupling term. First, the adjusted cosine similarity is defined to assess the similarity of the generalized trajectory with respect to the demonstrated trajectory. By optimizing the similarity, the trajectories can be generated in all situations. Next, by adding the force coupling term derived from adaptive admittance control to the transformation system of the original DMP, the controller achieves the force control ability. Then, the modified DMP-based robot control system is developed. The stability and convergence of the system are proved. Finally, the high precisions of the proposed method are verified by simulations and experiments. The method is significant for trajectory learning and generalization on the curved surface.

Mobile robots that can carry heavy loads play an important role in transporting and exploring in unstructured environment. However, there are some problems existing in conventional motor direct-drive robots such as excessive joint torque and unfoldable legs when they are under heavy loads. This paper proposes a tendon-actuated foldable wheeled-legged robot with high load-bearing capacity. A spreader is attached to the knee joint so that the output torque of the motor can be amplified by pulling the end of the spreader with a cable. The single and double fixed pulleys are used to reduce the required cable tension and avoid the interference of different cables, which can better achieve the folding of legs. In addition, the statics and kinematics of the tendon-actuated leg and the formulas for calculating the required tension and motor torque, as well as the relationship between foot velocity, joint speed, and motor speed are given. Finally, Matlab is used for simulation analysis, and it is found that the joint torques required for the tendon actuation are lower than for the direct actuation at the same joint angles.

A cable-driven segmented manipulator (CDSM) has superior dexterity for operations in confined space due to its light-slender body and redundant degree of freedoms (DOFs). However, its inverse kinematics resolving and configuration planning are very challenging due to the complex structure and strict constraints. In this article, we propose a two-layer geometric iteration (TLGI) method for inverse kinematics resolving and configuration-constrained Cartesian path planning. The computation efficiency is largely improved and singularities are avoided. First, the end-effector attitude is decomposed into a direction vector and a rotation angle. The former and the end-effector position are combined into state variables of the inner layer, and the latter is treated separately as the state variable of the outer layer. Then, the TLGI method enables to rapidly reach the desired 6-DOF pose by two-layer iterations, i.e., the inner and outer loop iteration. Second, during the inner loop iteration, the CDSM is modeled as an equivalent articulated arm whose end-effector position and direction is the same as that of CDSM, but its links length and joint angles depend on the current configuration of CDSM. Then, the efficient forward and backward reaching inverse kinematics (FABRIKs) method is extended to apply on CDSM so that it can fast reach the inner state variables. During the outer loop iteration, three different rotation cases, i.e., the rotating around the end, root, and both end and root, are designed to switch automatically to reach the outer state variable iteratively. Moreover, by parameterizing geometric constraints of the environment, a TLGI-based configuration-pose simultaneous planning method is also put forward to efficiently achieve additional configuration constraints for operations of CDSM in confined space. Finally, the proposed method is verified by both the simulations and experiments.

Continuum manipulators have shown a wide range of applications due to their inherent compliance and dexterity. At present, the cross-sectional dimension of these manipulators is often kept constant, which facilitates the design, fabrication and modeling processes. The famous piecewise-constant-curvature (PCC) assumption is widely used in the kinematics and motion control. By contrast, most natural creatures that have continuum structures usually exhibit variable cross sections, such as the elephant trunk and the octopus tentacle. Inspired by these creatures, variable cross-section continuum manipulators have been proposed in literature. For variable cross-section, the PCC assumption is no longer valid. In fact, the manipulator’s kinematics and statics are coupled, which should be considered and solved together. This paper establishes the general kinetostatic model of variable cross-section continuum manipulators, and performs experimental validations under various actuating and loading situations. Results showed that the proposed model has satisfactory accuracy in predicting the manipulator profile under various actuating and loading situations. The average root-mean-square error of the proposed model was 1.67 mm, and even the maximum error did not exceed 2.6 mm, according to all the 51 groups of tests on three 100 mm long prototypes. Furthermore, results also indicated that Type-1 manipulator (only varying the spacer dimension) has larger deflections and tends to be "softer" than Type-2 manipulator (only varying the backbone cross-sectional area). Results of this paper could be helpful for the design and analysis of variable cross-section continuum manipulators.

To go from human demonstration to robot independent operation, there are generally three phases of interaction to undergo, including human-robot interaction (HRI), human-robot-environment interaction (HREI), and robot-environment interaction (REI). Most existing methods address problems of a single stage. In this article, a unified neural adaptive control method that organically fuses multiple interactions is proposed. HRI, REI, and their coupling effects in HREI are comprehensively considered. First, the iterative least squares method is used for robot dynamics identification based on the linearized momentum observer. The accuracy of external force observation is improved to deal with dynamic uncertainties. The human force and the environmental force are achieved and decoupled by using only a force sensor, a momentum observer, and a selection matrix S. Next, the neural adaptive control method compensating position errors caused by the model uncertainty is addressed. The control system is proved to be stable based on the Lyapunov theorem. The trajectory tracking error under the model uncertainties is reduced. Then, the adaptive admittance control method is introduced. The interaction force of HRI is minimized and the interaction force control of REI is realized. Finally, the proposed method is verified by simulations and experiments.

Grasping unstructured objects and sensing the contact force are two vital issues for grippers. However, it is still difficult for most existing grippers to realize these two functions simultaneously. In this article, we revise the traditional fin-ray finger by inserting a series of rigid nodes into the compliant structure and develop an adaptive two-finger gripper. This design linearizes the gripper's deformation-force relationship and enables an intrinsic force sensing ability without any tactile sensor. Experimental results show that the finger has high accuracy in sensing the external force applied at its middle part (average error less than 3%) but much larger errors appear near its two ends. Further experiments indicate that the gripper functions well in sensing the total grasping force (average error less than 8%). Although larger errors are observed in estimating the force distribution at each node, the variation tendency of the sensed force coincides well with the ground truth. Experiments are also carried out on grasping free-form objects and performing pick-and-place operations to further prove the gripper's adaptive grasping and intrinsic force sensing abilities.

With many degrees of freedom (DOFs), a hyper-redundant manipulator has superior dexterity and flexible manipulation ability. However, its inverse kinematics and configuration planning are very challenging. With the increase in the number of DOFs, the corresponding computation load or training set will be much larger for traditional methods (such as the generalized inverse method and the artificial neural network method). In this paper, a segmented geometry method is proposed for a spatial hyper-redundant manipulator to solve the above problems. Similar to the human arm, the hyper-redundant manipulator is segmented into three sections from geometry, i.e., shoulder, elbow, and wrist. Then, its kinematics can be solved separately according to the segmentation, which reduces the complexity of the solution and simplifies the computation of the inverse kinematics. Furthermore, the configuration is parameterized by several parameters, i.e., the arm-angle, space arc parameters, and desired direction vector. The shoulder has proximal four DOFs, which is redundant for positioning the elbow and avoiding the joint limit. The arm-angle parameter is defined to solve the redundancy. The wrist consists of the distal two DOFs, and its joints are determined to match the desired direction vector of the end-effector. All the other joints (except for the joints belonging to shoulder and wrist) compose the elbow. These joint angles are solved by using space arc-based method. The configuration planning for avoiding joint limit, obstacles, and inspecting narrow pipeline are detailed for practical applications. Finally, circular trajectory tracking and pipeline inspection are, respectively, simulated and experimented on a 20-DOFs hyper-redundant manipulator. The results show that the proposed method can give solutions of the three-dimensional-pose-determining problem and the configuration-planning problem. The computation of the inverse kinematics is simplified for real-time control. It can also be applied to other spatial hyper-redundant manipulators with similar serial configurations.

Cable-driven segmented manipulators (CDSMs) featured by superior dexterity, light and slender body are excellent candidates for operations in confined environments. However, the stiffness and load capacity of such manipulators have been a challenge due to their structural elasticity. In this paper, we propose an improved mechanism design based on the preliminary work to enhance the linkage accuracy and arm continuity without sacrificing the dexterity, high stiffness and load capacity of CDSM. The manipulator is composed of 4 improved hybrid active-passive linkage segments. Its short and long linkage cables with pretension mechanism are designed to keep equal angles of adjacent joints. An improved separable small driving control box is also designed with both quick release and load mechanism and stroke amplification mechanism. Then the size of control box can still remain small, even the number of segments and the joint limit angles increase. Considering the improved in-segment linkage characteristic, traditional kinematic equations and Jacobian matrix are greatly simplified with Denavit-Hartenberg (D-H) method. Further trajectory tracking planning based on the simplified kinematics solved the Cartesian space planning for task design. Finally, a prototype system is developed to perform the linkage accuracy and comprehensive obstacle avoidance experiments. Experimental results show that the developed hybrid active and passive CDSM has relatively high accuracy and super dexterity.

In a multiarm space robotic system, one or more manipulators can be used to stabilize the base through counteracting the disturbance caused by other manipulators performing on-orbital tasks. However, singularities are inevitably present in the traditional methods based on differential kinematics solutions. In this paper, we propose a singularity-free trajectory planning method to simultaneously keep the attitude and centroid position of the base stabilized in inertial space; the balance arms are also designed. First, we derive the coupling motion equations of a free-floating multiarm space robotic system. Then, the singularity problems are theoretically analyzed, and the theoretical basis for singularity-free trajectory planning is established. Second, we decompose the six degrees of freedom pose (attitude and position) stabilization problem into two 3DOF subproblems related to attitude and position balancing. We then design two robotic arms: 1) a position balance arm and 2) an attitude balance arm, to maintain the base centroid position and attitude, respectively. Third, we plan the coordinated trajectories of the two balance arms according to holonomic and nonholonomic constraints. As long as the desired motion is not beyond its balance ability, the reasonable joint variables can always be determined without encountering a singularity problem. Finally, the proposed methods are verified using simulations of typical on-orbital missions, including joint trajectory tracking and target capturing.

For traditional manipulators, there is a large number of electrical cables between the motion controller and the joint servo controllers. It is very inconvenient for maintenance, update, and safe operation. In this paper, we develop a lightweight redundant manipulator with high stable wireless communication link and compliance control. The motion controller, servo controller, and communication link are taken as a whole system to be optimized. The manipulator body and the motion controller are physically separated. It is very helpful for building distributed networked-manufacturing system or intelligent manufacturing system for Industry 4.0. The control system can be quickly updated by changing the object's identification without reconnect the communication cables. The mechanical part of the manipulator contains modular joints and links. Each joint is integrated with hall sensors, an incremental magnetic encoder, an absolute magnetic encoder and current sensors. The electrical part includes a central controller, seven joint servo controllers, and a wireless communication module based on ZigBee. By designing the application layer protocol, the communication stability is improved. In order to achieve the force control requirements in fine operation like assembly. A wireless compliance control frame is then designed. The compliance control method is realized on the central controller, by which the generated control commands are sent to the joint servo controllers through a wireless link. The problems caused by large electrical cables are then solved. Finally, the prototype and the experimental system are developed. Some experiments are carried out, including wireless communication test, trajectory tracking experiments, load carrying experiments, and wireless impedance control experiments. Results verify the functions and performance of the developed 7-DOF manipulator.

With a light and slender body, a cable-driven redundant spatial manipulator (CRSM) has flexible manipulability and high maneuverability in confined environment. However, compared with revolute rigid manipulators, such type of manipulators generally has low stiffness and weak load capacity. In this paper, we propose a new mechanism design to improve the stiffness and load capacity without sacrificing the manipulator dexterity and the end-effector accuracy. The manipulator is composed of 3 active-passive-linkage segments and 1 active tool end-effector. Each active-passive segment has 2 degrees of freedom (DOFs) driven by three evenly distributed cables. Pretension mechanism and linkage cables are designed to keep strict equal angles of adjacent joints. A separable control box, which contains all the motors and cable transmission mechanisms is also designed with a quick release-and-lock mechanism. Therefore, the robotic arm can be easily removed and installed. Based on the equal angle characteristic, kinematic equations of manipulator are established with Denavit-Hartenberg (D-H) method and the Jacobian matrix is also simplified. Further analysis of the workspace supplies the guidance for the task design and motion planning. Finally, a prototype system is developed to perform the stiffness and load capacity experiments. Experimental results show that the developed CRSM has relatively high stiffness and load capacity.

Capturing a moving object with large momentum by a dual-arm robot is especially challenging because of the requirement of dual-arm coordinated motion planning for tracking the moving object, and the operational force control for contact and momentum transfer. In this paper, we present a dual-arm coordinated motion planning and compliance control method with a unique null-space projected relative Jacobian and relative operational force between the two arms. The proposed method is able to plan dual-arm capturing motion and control the capturing force without disturbing the tracking motion. We have also adopted a direct collocation trajectory optimization method to generate optimal trajectory to decrease the object's momentum with minimum effort. Simulation and experiment of dual-arm robots picking up a moving box on a mobile platform are carried out to verify the proposed method.

This article proposes a new approach to accomplish the mission of orbital transfer using the two finite variable thrusts. This problem requires attaining the two optimal time histories of the acceleration in the each thrust arc, which can be expressed as a polynomial function of time, and taking the corresponding coefficients as potential solutions can be obtained by using the particle swarm optimization technique. Furthermore, combining with penalty function method to solve the trajectory terminal constraints problems make final states completely free without and with rendezvous problem. Then, the optimal values of all the unknown parameters of the problem under considering the minimum fuel-consumption are obtained. Both the initial and final states of the trajectory are considered with unknown and known. In order to avoid collision with on-orbit spacecraft at the final orbit, the transfer trajectory should not be intersection with the final orbit except the final states. Finally, for the four trajectories optimization problems, the numerical results shown that the minimum-fuel can be obtained by considering the unknown or known coast arc.

A snake-like robot is a hyper-redundant robot. It has flexible movement ability and high stability with low center of gravity. It is very suitable for environment detection in the rugged road or narrow space. In this paper, a 16-DOFs snake robot is composed. It has ten 2-DOFs modular spherical-shape joints. The joints are arranged as the structure of "(Roll-Pitch)-(Roll-Pitch)-", where "(Roll-Pitch)" denotes a modularized 2-DOF joint, which can rotate along the roll and pitch axis. The exterior frame of each joint is designed as a spherical structure, which is connected with the motor through two stage reduction mechanism. Therefore, the drive torques are largely increased. Many small passive wheels are mounted along a circle of the exterior surface. Such design largely decrease the friction between the robot and the road. It also has more movement modes than the traditional design. We also develop the embedded controller based on the ARM processor and uc/os-ii real-time operation system. The gait planning algorithms are programmed using C language and realized in the embedded processor. At last, typical cases are experimented. The experiment results show that the developed robot has high mobility and flexibility.

In this paper, we developed a small wheel-legged mobile robot system, which could walk on different road environments using wheels or legs. It is composed of mechanical, sensor and control subsystems. The mechanical subsystem includes a wheel-legged mobile platform, a rigid robotic arm and a flexible arm. The mobile platform provides a variety of movement ways to meet the requirement of different mobility. The rigid arm (denoted by arm-a) is a serial manipulator with 4-DOFs. It can be used to grasp and manipulate payloads. The flexible arm (denoted by arm-b) is a manipulator with continuous curve, and a camera is mounted on arm-b. So it can be used to provide visual inspection and measurement information. The sensor subsystem is composed of ultrasonic sensors mounted on the platform and a WIFI camera mounted on arm-b. It provides measurement information and visual inspection for remote control. The control subsystem includes an embedded controller and a PC computer. The former is developed based on an ARM microprocessor, on which the real-time operation system-RT-Thread system runs. The mission decomposition and trajectory planning algorithms are programed in C language and run in the PC. At last, typical experiments are performed. Experiment results verified the robot's mobility, operation capability and remote-control function.

With the rapid development of robotics, dual-arm robots have been more and more widely used. Compared with the traditional single manipulator, it is very challenging for a dual-arm robot in modelling, planning and control. In this paper, we propose two compliance control methods for dual arm coordination to meet different requirements of fine manipulation tasks, such as payload carrying, assembly and repairing. The first method is called master-slave force control strategy, and the second is shared force control strategy. For the former, the desired trajectory and operational force of master arm are given in advance. Then that of slave arm are calculated from the closed-chain constraint equation. On the contrary, the two arms can be controlled in shared mode, that is to say, the desired trajectory and operational force of the end-effectors of dual arms are decomposed from the closed-chain constraint equation directly. The coordinated kinematic and dynamic equations of dual-arm robot system are established by considering the closed-chain constraint relationship. According to the force balance equation of the objective payload, the common force is decomposed into the desired end-effector force of each manipulator. Finally, the control algorithms are verified by simulation and experiment.

A snake-like robot is a hyper-redundant robot. It has flexible movement ability and high stability with low center of gravity. It is very suitable for environment detection in the rugged road or narrow space. This paper develops a snake-like robot with 10 degrees of freedoms (DOFs). Its joints are arranged as the structure of “Roll-Pitch-Roll-Pitch-....”, where “Roll” and “Pitch” respectively denote a Roll and Pitch joint. Each joint is designed as the same modularized unit, which can be used as a “Roll” or “Pitch” joint. Such design decreases the cost of development and enhances the flexibility of applications. Furthermore, the kinematics equation of this robot is derived and the movement ability is analyzed. Inspired by the biological behavior of a real snake, we plan several typical gaits for the snake-like robot, including peristalsis, rolling and Serpenoid curve gaits. We also develop the embedded controller based on the ARM processor and uc/os-ii real-time operation system. The gait planning algorithms are programmed using C language and realized in the embedded processor. At last, typical cases are experimented. The experiment results show that the developed robot has high mobility and flexibility.

This paper propose a practical and effective method for identifying the complete inertia parameters of a space robotic system. The key is the following steps: equivalent single-body identification, and equivalent two-body identification. For the former, all joints are locked into a normal configuration, and the thrusters are used for orbital maneuvering. The object function is defined from the view of acceleration and velocity. For the latter, only one joint is unlocked and driven to move along the exciting trajectory under the free-floating mode. The linear and angular momentum equations are used to define the object function. Hence, the parameter identification problem is transformed into a non-linear optimization problem, and the PSO algorithm is used to determine the optimal parameters. By sequentially unlocking the 1st to nth joint, the mass properties of body 0 to n are completely identified. The proposed method is general and can be easily extended for many cases.

Autonomous target capturing is the key for space robot to perform on-orbital servicing tasks. To meet the requirement of complex and long-term task, large flexible appendages, such as solar paddles and antenna reflectors are usually mounted on the base of a space robot. Due to the structure vibration, it is very challenging to capture a free-floating target satellite. In this paper, we derived the kinematics equations and proposed the autonomous target capturing method for free-floating flexible-base space robots. The kinematics equation established the mapping from the base velocities, joint rates and elastic motion to the end-effector velocities. Based on this equation, we designed resolved motion rate control with vibration compensation for the space manipulator. Another contribution of this paper is that we modeled the dynamic coupling between the rigid movement of the end-effector and the flexible vibration of the solar paddles. Based on this model, we analyzed the coupling effect which was very important for the design of the manipulator and determining the trajectory planning and control strategy. At last, a simulation system was created and simulation studies of the proposed methods were carried out. The simulation results verify the proposed methods.

Due to the dynamic interaction, the motion of the arms alters the attitude and position of the base. To stabilize the centroid position of the base during on-orbital manipulation, we proposed the modeling concept of the "Base Centroid Virtual Manipulator (BCVM)" for free-floating multi-arm space robotic systems. Correspondingly, the trajectory planning method of the balance arm was addressed. The movement direction and the position of each joint of the BCVM are the same as those of the real space manipulator (SM). The end-effector's position of the BCVM denotes the equivalent centroid of the corresponding SM. By resolving the position-level kinematic equations, the singularity-free trajectory of the balance arm was then planned. Based on the BCVM model, the stabilization ability of a given balance arm can be easily determined by analyzing the workspace of the BCVM. Furthermore, the configuration and the mass properties of the balance arm can be optimized. Simulation results of joint trajectory tracking task verified the proposed model and method.

The arm-angle was often used to parameterize the self-motion of S-R-S (Spherical-Revolute-Spherical) redundant manipulators when solving the inverse kinematics. However, there were some shortcomings for previous works: existing algorithm singularity or not suitable for configuration control. In this paper, we proposed an analytical resolution method based on dual arm-angle parameterization. Using two orthogonal vectors to define two absolute reference planes, we got two arm-angles which satisfy a specific condition. Since there is always at least one arm angle to represent the redundancy, the algorithm singularity problem does not exist. The “dual arm-angle” method keeps the advantages of “arm-angle”, and overcomes the shortcomings of the traditional methods. Another contribution of this paper is that we derived the absolute reference elbow attitude matrix0R3ψ=0, which is the key for the analytical inverse kinematics resolution but was not addressed in the previous paper. Simulation results for a general case and an algorithm singularity case verified the presented method.

The Canadarm2, also named Space Station Remote Manipulator System (SSRMS), is a 7-joint redundant manipulator. Without spherical wrists, the singularity analysis and avoidance of these manipulators are very difficult. In this paper, a method is presented to analytically identify its singular configurations based on the elementary transformation of Jacobian matrix. Firstly, we constructed a general kinematics model to describe them in a united manner. Correspondingly, the differential kinematics equation and the modified form are derived. Secondly, the singularity conditions are isolated and collected in a 3×4 sub-matrix by several times row transformation of the modified Jacobian matrix, which is partitioned into a block-triangle matrix. Finally, all the singularity configurations are determined by analyzing the rank degeneracy conditions of the 3×4 sub-matrix. The proposed method isolates the singularity conditions, and collects them in a 3×4 sub-matrix, largely reducing the computation workload.

Autonomous rendezvous in close range requires adequate ground simulations due to its significant difficulties and risks. In this paper, a novel semi-physical simulation system for binocular vision guided rendezvous is established. In this system, virtual three-dimensional models of the spacecrafts and the scene are created using computer graphic technology. Accordingly, images of the binocular cameras on board chaser (servicer) spacecraft are generated and displayed on the liquid crystal displays (LCDs). As the physical component in the simulation loop, two industrial cameras photograph the virtual images on the LCDs so that real camera noise is involved. In order to perform the closed-loop simulation, image acquisition, image processing, pose measurement, chaser guidance, navigation and control, and the system's dynamic motion are conducted. Through the combination of “virtual environment” and “physical environment”, the simulation system can successfully demonstrate binocular vision guided rendezvous. Simulation data is capable to verify the key algorithms during close range rendezvous. Changing the object model and dynamic model, this system can be applied to other vision-related researches.

Robotic systems are expected to play an increasingly important role in future space activities with the development of space technology. One broad area of application is in the servicing, construction, and maintenance of satellites and large space structures in orbit. Fine manipulation technology is very important for space robot to perform there tasks, since it must ensure safe and reliable interaction with objects or environment. In order to assure the task is accomplished successfully, ground experimentations are required for verifying key planning and control algorithms before the space robot is launched. In this paper, based on the concept of a hybrid approach combining the mathematical model with the physical model, a ground experiment system is set up, which is composed of two industrial robots, global and hand-eye visual equipments, six-axis force/momentum sensors, guide rail and four computers. Many control approaches of fine manipulation, such as compliance control, impedance control, hybrid force/position control, intelligent control, and so on, can be verified using this system. As an example, contour curves tracking experiment based on compliance control strategy is performed. Experiment results show that the ground system is very useful for verifying dexterous manipulation technology of space robot.

Space robotic system is expected to play an increasingly important role in repairing GEO (geostationary orbit) satellites in the future. To perform the servicing mission, the robotic system is firstly required to approach and dock with the target autonomously, for which the measurement of relative pose is the key. It is a challenging task since the existing GEO satellites are generally non-cooperative, i.e. no artificial mark is mounted to aid the measurement. In this paper, a method based on binocular stereo vision is proposed to estimate the pose of a GEO satellite in the final approach phase. It directly takes the natural circular feature on the GEO satellite as the recognized object. Correspondingly, an image processing and pose measurement algorithm is presented to determine the relative position and orientation of the target. This algorithm provides a closed-form solution using simple mathematics, therefore, it is suitable to space applications where the computation capability of the on-board processor is very limited. In addition, it effectively solves the orientation-duality problem for circular feature, requiring neither specific motions of the camera nor a priori knowledge about the radius of the circle. Computer simulations verify the proposed method.

Due to failure of mechanisms to deploy, some large communication satellites lost their ability and resulted in huge economic cost. A space robotic system is expected to perform the on-orbit repairing mission. It is a tremendous challenge to navigate a space robot in final approach since the targets are generally non-cooperative. Rectangle features, which are common in the configuration of a satellite, can be chosen as the recognized objects. However, these characters are very large. Limited by the FOV (field of view), a monocular camera can not supply enough information of the rectangles. In this paper, a method based on monocular camera is proposed to determine the attitude of a large non-cooperative target using a partial rectangle. Firstly, the relationship of a rectangle and circular points by camera is derived and fused. Secondly, the attitude measurement algorithm is acquired from the constraint and a virtual rectangle is reconstructed. Lastly, the algorithm is verified by mathematic simulations which are very close to reality. The results show the validity and flexibility of the proposed method.

The failures of GEO (Geostationary Orbit) spacecrafts will result in large economic cost and other bad impacts. In this paper, we propose a space robotic servicing concept, and present the design of the corresponding system. The system consists of a 7-DOF redundant manipulator, a 2-DOF docking mechanism, a set of stereo vision and general subsystems of a spacecraft platform. This system can serve most existing GEO satellites, not requiring specially designed objects for grappling and measuring on the target. The serving tasks include: (a) visual inspecting; (b) target tracking, approaching and docking; (c) ORUs (Orbital Replacement Units) replacement; (d) un-deployed mechanism deploying; (e) extending satellites lifespan by replacing its own controller. As an example, the servicing mission of a malfunctioned GEO satellite with three severe mechanical failures is presented and simulated. The results show the validity and flexibility of the proposed system.

Space target may move in various modes, such as free-floating, tumbling, and so on. In order to capture a space target, autonomous trajectory planning algorithm is studied. The base of the space robot is free-floating for the purpose of safety and saving the fuel. Firstly, the target feature is extracted based on the measured information via the hand-eye camera. Then the target pose (position and orientation) and velocity (linear velocity and angular velocity) relative to the end-effector are estimated using Kalman filtering technology. Thirdly, an autonomous trajectory planning approach is proposed for capturing an space target with unknown motion. Lastly, a semi-physical simulation system is established to verify the planning algorithm. The simulation results show that the algorithm is valid