# Research on Human-Robot Collaboration Method for Parallel Robots Oriented to Segment Docking
## 1 Introduction
examined motion stability concerns related to the Stewart platform, assessing their impact on control delays in practical applications [14]. [PERSON] et al. performed a dynamic coupling torque analysis using joint space dynamic models, defining the dynamic coupling strength coefficient. They analyzed dynamic coupling characteristics based on this coefficient, outlining the variation pattern within the necessary motion trajectories [15]. [PERSON] et al. formulated the comprehensive dynamic model of a six-degrees-of-freedom parallel robot, evaluating channel coupling in various typical robot poses [16]. The cited literature did not explore the impact of coupling relationships on control algorithms or suggest strategies to improve the response performance of parallel robot control algorithms. Consequently, improving the control precision and response speed in human-robot collaboration using parallel robots warrants further investigation. In the collaborative docking of segments, parallel robots bearing heavy aerospace segments experience unknown interaction forces, significantly influencing their motion stability. Robot instability can result in unforeseen movements, hence affecting assembly precision [17]. Thus, in human-robot collaboration, the robot's motion controller generally requires robust control integration. Multiple studies have proposed diverse robust control strategies. For example, [PERSON] et al. introduced a robust three-dimensional arm force estimation model, R3 DNet, based on a hybrid deep learning network, to establish a stable interaction interface, achieving a dependable human-robot collaborative performance [18]. [PERSON] et al. introduced the compliance dynamic system (CDS), a novel force control strategy. They rigorously validated CDS's stability using the Lyapunov stability theory, ensuring an accurate force control performance [19]. [PERSON] et al. presented performance enhancement after stability execution (PESE), a novel robust interaction control strategy. PESE guarantees robust, interactive stability in uncertain environments and ensures an effective contact performance [20]. [PERSON] et al. employed robust control on a KUKA robot, empowering the robot end-effector to manage variable and unknown loads for successful human-robot collaboration [21]. [PERSON] et al. suggested a robust fuzzy sliding mode control approach based on impedance, enhancing the robot system's ability to resist disturbances [22]. The aforementioned studies primarily concentrated on robust control research for conventional serial robots. However, for parallel robots, their closed-loop structure introduces indeterminate Coriolis and coupling terms in the dynamic model, rendering the robustness analysis more challenging in the presence of uncertainties. Consequently, attaining robust dynamic motion control remains an unresolved challenge when precise dynamic models for parallel robots are unattainable. Focusing on the current human-robot collaboration (HRC) strategy for parallel robots, issues arise regarding stability, the lack of flexibility, and the slow response speed during collaboration. This paper proposes a fractional-order variable damping admittance control (FVDAC) that adjusts the damping matrix within the admittance control system according to the interaction force exerted by the operator. Additionally, it establishes a functional relationship between the interaction force and the damping matrix, enabling the Stewart platform to discern the operator's intentions during collaborative assembly, and dynamically adjusting its velocity. Concurrently, fractional-order control significantly enhances the controller's response performance. This can be used to tackle the issue of inadequate motion stability in parallel robots caused by unknown interaction forces during collaboration, consequently impacting assembly quality. This paper introduces an inverse dynamic robust control mechanism to enhance the motion controller's robustness against unknown interaction forces.