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arXiv 1005.5035cs.RO
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足式机器人的动力学运动建模

Dynamic Motion Modelling for Legged Robots

University of Bremen(不来梅大学)

Mark Edgington, Yohannes Kassahun, Frank Kirchner

摘要:

精确的运动模型是现代机器人系统的重要组成部分,但为复杂系统构建这样的模型通常需要大量的手动工作。在本文中,我们提出了一种运动模型表示,动态高斯混合模型(DGMM),它说明了需要手动设计的运动模型的形式,并提供了一个直接的手段,将辅助传感器数据到模型中。这种表示及其伴随的算法进行了实验验证,使用8腿运动学复杂的机器人,以及标准的基准数据集。所提出的方法不仅学习机器人的运动模型,但也提高了模型的准确性,通过结合周围的地形信息的机器人。

英文摘要:

An accurate motion model is an important component in modern-day robotic systems, but building such a model for a complex system often requires an appreciable amount of manual effort. In this paper we present a motion model representation, the Dynamic Gaussian Mixture Model (DGMM), that alleviates the need to manually design the form of a motion model, and provides a direct means of incorporating auxiliary sensory data into the model. This representation and its accompanying algorithms are validated experimentally using an 8-legged kinematically complex robot, as well as a standard benchmark dataset. The presented method not only learns the robot's motion model, but also improves the model's accuracy by incorporating information about the terrain surrounding the robot.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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