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Trajectory Optimization for High-Power Robots with Motor Temperature Constraints

机译:具有电机温度约束的大功率机器人的轨迹优化

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Modeling heat transfer is an important problem in high-power electrical robots as the increase of motor temperature leads to both lower energy efficiency and the risk of motor damage. Power consumption itself is a strong restriction in these robots especially for battery-powered robots such as those used in disaster-response. In this paper, we propose to reduce power consumption and temperature for robots with high-power DC actuators without cooling systems only through motion planning. We first propose a parametric thermal model for brushless DC motors which accounts for the relationship between internal and external temperature and motor thermal resistances. Then, we introduce temperature variables and a thermal model constraint on a trajectory optimization problem which allows for power consumption minimization or the enforcing of temperature bounds during motion planning. We show that the approach leads to qualitatively different motion compared to typical cost function choices, as well as energy consumption gains of up to 40%.
机译:对传热进行建模是大功率电动机器人中的一个重要问题,因为电动机温度的升高会导致能源效率降低和电动机损坏的风险。功耗本身是这些机器人的一个强大限制,尤其是对于电池供电的机器人(例如在灾难响应中使用的机器人)而言。在本文中,我们建议仅通过运动计划来降低不带冷却系统的大功率直流执行器的机器人的功耗和温度。我们首先为无刷直流电动机提出一个参数热模型,该模型考虑了内部和外部温度与电动机热阻之间的关系。然后,我们介绍了关于轨迹优化问题的温度变量和热模型约束,该轨迹优化问题允许在运动计划过程中将功耗最小化或强制执行温度范围。我们证明,与典型的成本函数选择相比,该方法导致的运动在质量上有所不同,并且能耗增加了40%。

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