本文以自动化立体仓库物流环境下的自动存取为背景，研究8索驱动并联机构在该领域的应用。采用索驱动并联机构实现货物自动化存取中的堆垛功能，解决仓储货物在堆垛过程的准确性和稳定性问题，开展包括索驱动机器人基本模型建立、运动学自标定和振动抑制等三方面的研究工作，为实际应用奠定理论基础。具体内容如下：针对设计的用于仓储环境堆垛任务的索驱动并联机器人，开展对基本运动性能和控制策略的研究。建立机构的运动学和动力学模型，通过解算关键运动指标分析运动的可行性，利用2-范数方法完成索力优化分析，并设计一种基于PID控制的索力控制方法。根据运动学逆解和索力控制方案，提出位置驱动和力矩跟随的力位混合控制策略，通过驱动索和跟随索的协同工作实现仓储机器人的运动控制，并完成总体方案设计。针对堆垛作业停放状态的精度问题，提出一种基于视觉相机测量的运动学自标定方案。基于系统误差源分析，建立仓储机器人末端位姿与机构模型之间的关系，由误差模型推导对应参数辨识方程，提出一种先简化后补偿的标定策略，通过最小二乘法辨识相关运动学参数，最后通过误差拟合的方式补偿算法适应性。结合货格单元网格化布局特点，提出采用视觉相机识别靶标二维码的动平台位姿测量方法。通过模型仿真验证辨识算法有效性，并进行样机实验验证自标定效果。针对堆垛作业状态切换时的稳定性问题，对索驱动仓储机器人的振动特性和抑振策略展开研究。基于绳索的微元性质，通过有限元方法和牛顿运动定律分析绳索和机构的振动状态，先后建立单根绳索和索并联机构的振动模型，并进行刚度分析，研究影响系统振动特性的因素，通过实验探究相关因素对系统的影响规律，总结相应的抑振策略。基于开展的理论研究工作，建立仓储机器人的仿真模型，由功能需求确定各单元的相互关系，对关键元件进行设计和选型。根据仓储机器人设计方案，搭建实验室尺度下的样机装置，基于该装置完成了视觉自标定的验证实验，以及抑制振动效果的实验。
Based on the background of automatic storage and retrieval in warehouse logistics environment, this paper studies the application of 8-cable-driven parallel mechanism in this field. The cable driven parallel mechanism is used to realize the stacking tasks of automatic goods storage and retrieval, to maintain the accuracy and stability of storage goods in the stacking process. The research work includes the basic model establishment, kinematics self-calibration and vibration suppression of the cable driven robot, which lays a theoretical foundation for practical application. The details are as follows:Aiming at the cable driven parallel robot designed for stacking task in storage environment, the basic motion performance and control strategy are studied. The kinematic and dynamic models of the mechanism are established, and the feasibility of motion is analyzed by solving the key motion indicators. The cable force optimization analysis is completed by using the 2-norm method, and a cable force control method based on PID control is designed. According to the inverse kinematics solution and cable force control scheme, a hybrid control strategy of position driving and torque following is proposed. Through the cooperative work of driving cable and following cable, the motion control of storage robot is realized, and the overall scheme design is completed.Aiming at the accuracy problem of stacking operation, a kinematic self-calibration scheme based on vision camera measurement is proposed. Based on the analysis of the system error source, the relationship between the end pose and the mechanism model of the storage robot is established. The corresponding parameter identification equation is derived from the error model. A calibration strategy of simplification before compensation is proposed. The relevant kinematic parameters are identified by the least square method. Finally, the adaptability of the algorithm is compensated by the way of error fitting. Combined with the grid layout characteristics of cargo cells, a moving platform pose measurement method based on visual camera recognition target two-dimensional code is proposed. The effectiveness of the identification algorithm is verified by model simulation, and the self-calibration effect is verified by prototype experiment.Aiming at the problem of stability when the stacking operation state changes, the vibration characteristics and vibration suppression strategy of the cable driven storage robot are studied. Based on the micro element properties of the rope, the vibration state of the rope and mechanism is analyzed by the finite element method and Newton's law of motion. The vibration models of single rope and cable parallel mechanism are established successively, and the stiffness analysis is carried out to study the factors affecting the vibration characteristics of the system. The influence laws of the relevant factors on the system are explored through experiments, and the corresponding vibration suppression strategies are summarized.Based on the theoretical research work, the simulation model of storage robot is established, the relationship of each unit is determined by the functional requirements, and the key components are designed and selected. According to the design scheme of storage robot, a laboratory-scale prototype device is built. Based on the device, the verification experiments of visual self-calibration and vibration suppression effect are completed.
