The flexible-joint robot has superior attractive features because of its high mobility, high load ratio, high torque fidelity, robustness for external disturbance, task adaptability, and safety. In this article, an autonomous mobile manipulator driven by the designed series elastic actuators is developed. A complete dynamic model of a nonholonomic mobile manipulator including a mobile platform and a manipulator with joint flexibility operating simultaneously is proposed. An integrated whole-body trajectory control framework is proposed for such robot to perform mobile manipulation tasks. Considering the nonholonomic and holonomic constraints in the mobile manipulation, the whole-body dynamics is formulated and reduced. To address the highly nonlinear of the dynamics and model uncertainty, a novel integral Lyapunov function based adaptive neural network control for task tracking under uncertainties of the flexible-joint robot model is proposed. Compared with existing methods, the proposed method provides an alternative for controlling flexible-joint robots. The feasibility of the proposed method is verified by the extensive trajectory tracking experiment results in our developed flexible joint manipulator.

中文翻译：

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使用系列弹性执行器的自主移动机械手的整体控制

柔性关节机器人具有高移动性，高负载率，高扭矩保真度，对外部干扰的鲁棒性，任务适应性和安全性，因此具有卓越的吸引力。在本文中，开发了由设计的系列弹性致动器驱动的自主移动机械手。提出了一种非完整的移动机器人的完整动力学模型，该模型包括一个移动平台和一个同时具有关节柔性的机器人。针对这种机器人执行移动操纵任务，提出了一种集成的全身轨迹控制框架。考虑到移动操作中的非完整性和完整性约束，制定并减少了全身动力学。为了解决动力学和模型不确定性的高度非线性问题，提出了一种新的基于李雅普诺夫积分函数的自适应神经网络控制的柔性关节机器人模型不确定性任务跟踪。与现有方法相比，该方法为控制柔性关节机器人提供了一种选择。在我们开发的柔性关节机械手中广泛的轨迹跟踪实验结果验证了该方法的可行性。