Fast object approximation for real-time 3D obstacle avoidance with biped robots
Fast object approximation for real-time 3D obstacle avoidance with biped robots
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DOI：
10.1109/aim.2016.7576740
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发表时间：
2016-07
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影响因子：
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通讯作者：
Daniel Wahrmann;Arne-Christoph Hildebrandt;Robert Wittmann;Felix Sygulla;D. Rixen;Thomas Buschmann
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文献类型：
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作者：
Daniel Wahrmann;Arne-Christoph Hildebrandt;Robert Wittmann;Felix Sygulla;D. Rixen;Thomas Buschmann
为了实现完全自主的仿人导航，环境感知必须足够快，以便在动态环境中进行实时规划，并且对先前未知的场景具有鲁棒性。我们提出了一个开源的，灵活的和高效的视觉系统，代表动态环境，使用简单的几何形状。它仅基于机载传感和3D点云处理，在机器人移动时使用扫掠球体积来近似物体。它不依赖于颜色或任何以前的模型或信息。我们通过在我们的人类大小的机器人Lola上测试来证明我们方法的可行性，该机器人能够在以0.4m/s的设定速度行走时实时避免移动障碍物，并执行全身碰撞避免。
In order to achieve fully autonomous humanoid navigation, environment perception must be both fast enough for real-time planning in dynamic environments and robust against previously unknown scenarios. We present an open source, flexible and efficient vision system that represents dynamic environments using simple geometries. Based only on onboard sensing and 3D point cloud processing, it approximates objects using swept-sphere-volumes while the robot is moving. It does not rely on color or any previous models or information. We demonstrate the viability of our approach by testing it on our human-sized biped robot Lola, which is able to avoid moving obstacles in real-time while walking at a set speed of 0.4m/s and performing whole-body collision avoidance.