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Constrained multi-objective trajectory planning of parallel kinematic machines

机译:并联运动机的约束多目标轨迹规划

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This paper presents a new approach to multi-objective dynamic trajectory planning of parallel kinematic machines (PKM) under task, workspace and manipulator constraints. The robot kinematic and dynamic model, (including actuators) is first developed. Then the proposed trajectory planning system is introduced. It minimizes electrical and kinetic energy, robot traveling time separating two sampling periods, and maximizes a measure of manipulability allowing singularity avoidance. Several technological constraints such as actuator, link length and workspace limitations, and some task requirements, such as passing through imposed poses are simultaneously satisfied. The discrete augmented Lagrangean technique is used to solve the resulting strong nonlinear constrained optimal control problem. A decoupled formulation is proposed in order to cope with some difficulties arising from dynamic parameters computation. A systematic implementation procedure is provided along with some numerical issues. Simulation results proving the effectiveness of the proposed approach are given and discussed.
机译:本文提出了一种在任务,工作空间和机械手约束下的并联运动机(PKM)多目标动态轨迹规划的新方法。首先开发了机器人的运动学和动力学模型(包括执行器)。然后介绍了拟议的弹道规划系统。它最大程度地减少了电能和动能,使机器人的行进时间分隔了两个采样周期,并且最大限度地提高了可操作性,从而避免了奇异现象。同时满足一些技术约束,例如致动器,连杆长度和工作空间限制,以及一些任务要求,例如通过施加的姿势。离散增强拉格朗日技术用于解决由此产生的强非线性约束最优控制问题。为了解决动态参数计算带来的一些困难,提出了一种解耦公式。提供了系统的实施程序以及一些数字问题。仿真结果证明了该方法的有效性。

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