A biarc fitting algorithm is proposed for the designed concentric cable-driven manipulator working in oropharyngeal (OP) swab samplings. This algorithm makes the concentric cable-driven manipulator composed of discrete nodes have a high degree of fit with the continuous curve planned by the biarc method. Three advantages of this algorithm are as follows. First of all, by adjusting the tangent at the end point, the problem of large deviation fitting between the actual path and the planned path caused by the fixed tangent at the end point during path tracking is solved. In addition, by adjusting the given starting point, the problem of large deviation fitting between the concentric cable-driven manipulator and biarc curve caused by non-integer number of nodes during configuration fitting is solved. Further, by adjusting the proportionality coefficient, the problem of large deviation fitting between the concentric cable-driven manipulator and biarc curve caused by the odd-even variation of the number of moving nodes during configuration fitting is solved. Tracking the planned paths of OP-swab sampling, the simulation and experiment verify the effectiveness of the biarc fitting algorithm for concentric cable-driven manipulators working in OP-swab samplings.Note to Practitioners—This paper is motivated by the requirement of effective planning for a concentric cable-driven manipulator composed of discrete nodes working in automatic oropharyngeal-swab samplings. Existing planning methods make it difficult to fit a concentric cable-driven manipulators composed of discrete nodes to the planned continuous curve. In this paper, we propose a biarc fitting algorithm to improve the degree of fit between cable-driven manipulator composed of discrete nodes and the planned continuous curve. This algorithm makes the concentric cable-driven manipulator composed of discrete nodes have a high degree of fit with the continuous curve planned by the biarc method. Three key factors of this algorithm to be optimized are the tangent at the end point, given starting point and proportionality coefficient. The simulation and experiment verify the effectiveness of the biarc fitting algorithm. In the future work, we will study the modelling based on variable-stiffness control and force feedback control of concentric cable-driven manipulators. This method can be used not only for concentric cable-driven manipulators working in the medical field, but also for cable-driven manipulators composed of discrete nodes inspecting and maintaining in aerospace, nuclear power plant and other similar fields.

Owing to the flexibility and redundancy, concentric cable-driven manipulators are widely used in confined space applications. However, it is challenging to establish shape prediction or force sensing for this type of manipulator. This paper proposes a static modeling method to address the shape prediction or force sensing challenges of concentric cable-driven manipulators. The Newton-Euler method is adopted to establish the static model of the concentric cable-driven manipulator with consideration of friction. On the one hand, the static model can accurately predict the shape when the external load and cable tension of the concentric cable-driven manipulator are known. On the other hand, the static model can also assist force sensing when the cable tension and shape of the concentric cable-driven manipulator are known. Finally, the accuracy of the shape prediction and force sensing of this model are both verified by experiment, separately. The results show that the accuracy of shape prediction is 95% and the accuracy of force sensing is 90%. The model is thus suitable for the shape prediction or force sensing of the concentric cable-driven manipulator. In addition, the errors associated with shape prediction or force sensing were found to be significantly reduced when the influence of friction was taken into account. Therefore, the proposed static modeling method considering friction is effective for the shape prediction or force sensing of concentric cable-driven manipulators. Note to Practitioners—Concentric cable-driven manipulators featured by small size and high flexibility are excellent candidates for operations in confined environments. This paper proposes a static modeling method to address the shape prediction or force sensing challenges of concentric cable-driven manipulators. The shape prediction can be used to facilitate the accurate positioning and control of such manipulators in various situations. The force sensing can be used to avoid unnecessary harm within the working environment of such manipulators. It is beneficial to promote the application of such manipulators in minimally invasive surgery, pharyngeal swab sampling, and other fields. Moreover, the static method applies not only to the specific model of a concentric cable-driven manipulator but also to various cable-driven manipulators. Similarly, the importance of the static model is not only that it improves the accuracy of shape prediction or force sensing but also that it can be applied to automation control of motion, flexibility, and stiffness.

The concentric cable-driven manipulator has characteristics of flexibility and slenderness when working in confined space. However, how to optimize a structure with appropriate stiffness becomes an important issue. In this paper, a structure optimization method based on stiffness model is proposed for the designed concentric cable-driven manipulator with three segments. Firstly, according to the characteristics of the cable and center support, the concentric cable-driven manipulator with three segments is designed in this paper. The concentric cable-driven manipulator addresses flexibility and active regulation of cable tension. Secondly, the stiffness modeling of the concentric cable-driven manipulator with three segments is carried out by introducing the concept of unit module. The stiffness of the concentric cable-driven manipulator is adjusted by optimizing cable diameters. Finally, the stiffness of C-shaped and S-shaped configurations are analyzed and compared. The analysis and experimental results can provide reference for structural optimization in practical applications.

This article presents a segment-progress statics method for configuration prediction or force sensing of concentric cable-driven manipulators. First, the statics model of the whole system was constructed by progressively analyzing from local segments to the whole. This statics modeling method reduces the complexity of the model and considers the most common forces and moments. Second, a solving flow is proposed based on the iteration-correction strategy for configuration prediction or force sensing. This strategy provides a new idea for the analysis of the static friction direction when the statics model is used for quasi-static prediction. Simulations and experiments show that the proposed segment-progress statics method is effective for configuration prediction or force sensing of concentric cable-driven manipulators. Moreover, the effect of the friction gain on the accuracy of statics model is found by analyzing the curvature of the manipulator. The piecewise constant curvature (PCC) assumption is also concluded to be only applicable to small end forces but not to large end forces for concentric cable-driven manipulators.

Concentric cable-driven manipulators have the flexibility and typical advantages of working in confined environments. However, its configuration optimization in confined three-dimensional (3-D) space is very complicated due to infinite configurations of inverse kinematics solutions. This article proposes a spatial triarc planning method in response to the issue mentioned above. A reasonable triarc configuration can be optimized by this method based on six input parameters, i.e., the proximal control point and tangent vector, distal control point and tangent vector, and two centers of curvature circles in both two-dimensional (2-D) and 3-D space. This method has the following three advantages. First, the task configuration of a spatial triarc can be predicted by presetting the relationship between the proximal and distal tangent vectors. Furthermore, the configuration of the middle and inner concentric cable-driven mechanism can be controlled by adjusting the direction of the distal tangent vector. Additionally, the proportion of each concentric cable-driven mechanism can be controlled by changing centers of curvature circles. Finally, the proposed spatial triarc planning method is verified by simulations and experiments. Results show that the maximum errors of the C-shaped spatial triarc and the S-shaped spatial triarc experiments are 1.68 mm and 1.36 mm, respectively.

The concentric cable-driven manipulator (CCDM) has the characteristics of high dexterity, light weight, and safe movement, making them widely used in confined spaces. However, there are difficulties in the fine control with proper stiffness of CCDMs due to their flexible structures and various configurations. This article proposes an analytical variable-stiffness method for the fine control of CCDMs. First, the stiffness model is established by taking into account key factors, including the middle elastic backbone, cable tensions, configurations, and external loads. Then, the stiffness mesh is generated based on the stiffness model, which visually represents changing trends of its stiffness. Simultaneously, the stiffness of CCDMs can be accurately adjusted by optimizing their configurations and cable tensions. Therefore, the fine control with high or low stiffness of CCDMs can be realized in practical applications. Finally, experiments are conducted to verify the analytical variable-stiffness method of CCDMs. Results indicate that the average error of the stiffness model is 5.42%. It also confirms the effectiveness of the proposed method for achieving analytical variable-stiffness control of CCDMs. Furthermore, the proposed method is also applicable to cable-driven manipulators with similar structures.

Superior dexterity and extreme flexibility are typical advantages for concentric cable-driven manipulators working in confined spaces. However, its inverse kinematics and configuration planning are very complicated. In this article, we propose a spatial biarc method for the above problem. The distinguishing feature of this method is that input parameters are two positions and two direction vectors in three-dimensional (3-D) space, and the output is a reasonable spatial biarc for controlling a concentric cable-driven manipulator in 3-D space. This method has the following three advantages. First, the positions and direction vectors of the base and inner distal tip are considered simultaneously. In addition, the length and ratio of the overlapped section and separated section can be adjusted by changing the length of the direction vectors. Furthermore, by judging the angular value of the direction vectors, one can predetermine whether the spatial configuration of the entire arm is C- or S-shaped. The proposed method realizes the parameterization of a concentric cable-driven manipulator, which makes it convenient to intuitively control the manipulator to achieve interference-free motion trajectory planning in confined spaces. Finally, trajectory tracking inspections are simulated and experimentally executed. It can be seen from results that the proposed spatial biarc method can provide reasonable solutions for concentric cable-driven manipulators. The method is especially favorable in terms of 3-D-pose-determination problem and trajectory-planning problem. It can also be applied to other manipulators with similar configurations. Without loss of generality, when the given points and direction vectors are coplanar, the proposed spatial biarc method can be transformed to a planar biarc method.

Driven by the SARS-CoV-2 pandemic, demand for oropharyngeal swab sampling (OP-swabs) is surging. However, medical staff can easily become infected by the virus during the sampling process. In an effort to combat this, we developed a novel, intrinsically safe rigid- flexible coupling (RFC) manipulator to improve the safety and reliability of OP-swab sampling to test for COVID-19, which is presented herein. Suitable sampling areas and the necessary contact force for OP-swab sampling tasks are carefully investigated, and three typical sampling paths outlined that could be performed by a robotic system. This is followed by a detailed description of an intrinsically safe bionic micro-pneumatic actuator (MPA) that was designed and fabricated as the main component of the RFC manipulator. The developed RFC manipulator’s kinematic modeling, motion planning, and force control capacities were designed for OP-swab sampling scenarios. The system was then validated using both an oral cavity phantom and human volunteers, with comparative experiments on the swab quality of the OP-swab sampling approach conducted in both robotic and manual modes. The results indicate that fully-automated sampling based on this design would be feasible.

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.

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.

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.