With continuously increasing requirements for physical human-robot interaction (pHRI), cable-driven parallel robots (CDPRs) have emerged as outstanding systems for its implementation due to the sufficient motion workspace and inherent cable flexibility. In particular, their modular structure facilitates straightforward reconfiguration. Inspired by this, this paper aims to enhance the dynamic characteristics of CDPRs during pHRI through online reconfiguration, so as to achieve the interaction performance improvement based on human intent. A novel metric, the mixed interaction wrench margin (MIWM), is first proposed to determine the optimal reconfiguration. This metric is devised by integrating the interaction force characteristics with CDPR inherent workspace properties, while explicitly considering the leading role of human intent. Subsequently, an adaptive-interaction-based reconfiguration strategy is established that the configuration can be arbitrarily changed by cable anchors, enabling compliant and adaptive pHRI. Informed by the actual interaction frequency, the strategy implements an asynchronous adjustment with different periods for configuration change and platform movement to achieve online optimization for reconfiguration. Finally, simulations and experiments conducted on different CDPR configurations with multiple pHRI tasks indicate that this strategy provides humans with more freedom, allowing them to exert more casual interaction forces, receive a quicker interactive response, and operate in a larger workspace.

The simple and modular structure of cable-driven parallel robots (CDPRs) can enable effective real-time reconfiguration. In this paper, an online reconfiguration strategy is proposed for a 3-DOF point-mass CDPR to adjust the cable anchor positions and enhance its performance in physical human-robot interaction (pHRI). The reconfiguration problem, inclusive of all relevant constraints such as the wrench feasible condition (WFC) and the structural constraint on the cable anchors, is formulated as a non-convex optimization problem to determine the optimal positions of cable anchors. However, such original formulation poses a serious challenge to real-time determination, primarily due to the non-convex constraint imposed by the WFC and the non-convex objective function. To address this issue, the characteristics of the CDPR are considered, and a linear approximation method is employed to simplify the original optimization problem into a linear one, allowing it to be efficiently solved by the dual simplex method. Additionally, an artificial potential field (APF) is designed, considering both the inherent workspace properties and the interaction force, to adjust the solution of the linear optimization problem, which ensures that the optimal solution remains within a safe distance from the boundary of the solution space. Simulations validate the effectiveness of the strategy in improving the interaction metric while satisfying constraints.

Low stiffness in 7-DOF cable-driven humanoid manipulators limits their precision, posing a significant challenge in complex human-robot interaction (HRI) scenarios. This paper presents a motion planning framework to enhance manipulator stiffness for both single and dual-arm configurations. For a single arm, we introduce a novel method that integrates dynamic obstacle avoidance with posture optimization to maximize end-effector stiffness. For dual-arm systems, we develop a coupled stiffness model that addresses inter-arm dynamics to improve performance in coordinated tasks. Experimental results on prototypes confirm that the proposed methods significantly reduce end-effector deviation under load, thereby improving the precision and reliability of these manipulators in sophisticated collaborative applications.

Owing to their lightweight design and structural flexibility, cable-driven dual-arm manipulators offer significant advantages in collaborative tasks. However, practical applications pose several challenges. The existence of environmental obstacles and the closed kinematic chain considerably increase the complexity of path planning. Furthermore, the inherently low stiffness of cable-driven systems can result in end-effector deformation, thereby reducing precision during path-following tasks. This paper proposes an adaptive, sampling-based path planning algorithm that addresses obstacle avoidance and closed kinematic chain constraint, facilitating efficient path planning in diverse operational environments. Additionally, an evaluation metric for the Cartesian stiffness of cable-driven dual-arm manipulators is introduced and incorporated into the proposed algorithm for optimization. This approach enhances both Cartesian stiffness and end-effector precision, thereby improving the reliability and accuracy of cable-driven dual-arm manipulators in practical applications.

Five-hundred-meter aperture spherical radio telescope (FAST) is a very famous large-scale scientific facility with excellent performance for astronomical observation in the world, but it currently fails to observe the center of the Milky Way Galaxy due to the limited observation angle that is affected by the heavy weight of the feed cabin. To improve this problem, an upgraded feed mechanism (UFM) with a lighter cable structure is designed and employed to replace the existing heavy rigid A-B rotator and Stewart platform in the feed cabin of FAST. The structural dimension of the UFM is analyzed and optimized under cable tension constraints to meet the requirements of the observation angle. Then, a novel disturbance increment method is proposed to analyze the anti-disturbance ability of the UFM, where a gradually increased disturbance wrench is applied to the UFM with the stiffness matrix iteratively updated. Through the dimensional optimization and further anti-disturbance analysis, the newly-designed UFM can indeed meet the higher demand for astronomical observation with the larger observation angle, which benefits from the lightweight cable structure. Besides, the UFM also has the appreciable anti-disturbance ability for long-term stable operation of FAST.

Achieving high-precision position control while maintaining positive cable tensions is the most challenging issue for the motion control of cable-driven parallel robots, which should be considered significantly. Different from the existing control schemes with online tension distribution that needs real-time computing in each control cycle, a novel dual-loop dynamic control scheme is proposed in this article, where a paralleled dual-loop tracking strategy is introduced to provide a more compatible scheme, which consists of two tracking loops: 1) the tension control loop and 2) the position control loop. In the former loop, the offline tension distribution is adopted to avoid cable hanging loosely and the real-time feasibility of the distribution method is no longer a necessary demand. In the latter loop, due to the complex dynamics characterized by the cable-driven form, the cooperative motion relation among multiple cables and inevitable external disturbances are investigated comprehensively, and the robust synchronization method is included to guarantee the high-precision position control. Afterward, the Lyapunov method is adopted to analyze the strict stability of the whole closed-loop system with both the position and tension control feedback. The experiments indicate that by synthesizing the two control loops, the proposed scheme can dramatically reduce the tracking errors in the trajectory tracking while avoiding the cable relaxation, and particularly, has a satisfactory control effect when the velocity and acceleration of the trajectory have significant oscillations. Additionally, the strong disturbance rejection ability is also validated via robustness experiments.

Cable-driven parallel robots (CDPRs) are a new type of parallel robots that use cables to control a mobile platform. They possess several advantages, including large workspace, low inertia, and high payload capacity. However, there are several problems in the high-precision trajectory tracking control of CDPRs. On the one hand, all the cables must remain in tension during the entire motion process. On the other hand, the controller design is subjected to model uncertainties and external disturbances. Accordingly, this article proposes a robust synchronization control (RSC) scheme in the cable length space to achieve high-precision trajectory tracking. The synchronization control ensures motion coordination among all the cables and prevents cable relaxation, whereas the robust control eliminates modeling errors and restrains external disturbances. The uniformly ultimate boundedness of the tracking and synchronization errors in the closed-loop system equation was proved using the Lyapunov theory. Simulations and experiments of the trajectory tracking control were both implemented on a three-degree-of-freedom CDPR. Compared with the adaptive robust control scheme and the augmented proportional derivative scheme on the premise of the approximate energy consumption, the proposed RSC scheme could reduce not only the tracking errors of the cables but also the synchronization errors between adjacent cables. Moreover, the RSC scheme could significantly improve the trajectory tracking accuracy of the mobile platform. The robustness of this scheme was verified using load experiments and torque-disturbance experiments.