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A Distributed Predictive Control Approach for Cooperative Manipulation of Multiple Underwater Vehicle Manipulator Systems

机译:多水下机器人操纵系统协同操纵的分布式预测控制方法

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This paper addresses the problem of cooperative object transportation for multiple Underwater Vehicle Manipulator Systems (UVMSs) in a constrained workspace involving static obstacles. We propose a Nonlinear Model Predictive Control (NMPC) approach for a team of UVMSs in order to transport an object while avoiding significant constraints and limitations such as: kinematic and representation singularities, obstacles within the workspace, joint limits and control input saturations. More precisely, by exploiting the coupled dynamics between the robots and the object, and using certain load sharing coefficients, we design a distributed NMPC for each UVMS in order to cooperatively transport the object within the workspace's feasible region. Moreover, the control scheme adopts load sharing among the UVMSs according to their specific payload capabilities. Additionally, the feedback relies on each UVMS's locally measurements and no explicit data is exchanged online among the robots, thus reducing the required communication bandwidth. Finally, real-time simulation results conducted in UwSim dynamic simulator running in ROS environment verify the efficiency of the theoretical finding.
机译:本文解决了在涉及静态障碍物的受限工作空间中,多个水下航行器机械手系统(UVMS)的协作对象运输问题。我们为一组UVMS提出了一种非线性模型预测控制(NMPC)方法,以便在运输对象时避免显着的约束和限制,例如:运动学和表示奇异性,工作空间内的障碍物,关节极限和控制输入饱和度。更准确地说,通过利用机器人与对象之间的耦合动力学,并使用一定的负载分配系数,我们为每个UVMS设计了一个分布式NMPC,以便在工作区的可行区域内协同运输对象。此外,该控制方案根据UVMS之间的特定负载能力采用负载分担。此外,反馈依赖于每个UVMS的本地测量,并且在机械手之间不会在线交换任何明确的数据,从而减少了所需的通信带宽。最后,在ROS环境下运行的UwSim动态仿真器中进行的实时仿真结果验证了理论发现的有效性。

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