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Group Surfing: A Pedestrian-Based Approach to Sidewalk Robot Navigation

机译:团体冲浪:基于行人的人行道机器人导航方法

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In this paper, we propose a novel navigation system for mobile robots in pedestrian-rich sidewalk environments. Sidewalks are unique in that the pedestrian-shared space has characteristics of both roads and indoor spaces. Like vehicles on roads, pedestrian movement often manifests as linear flows in opposing directions. On the other hand, pedestrians also form crowds and can exhibit much more random movements than vehicles. Classical algorithms are insufficient for safe navigation around pedestrians and remaining on the sidewalk space. Thus, our approach takes advantage of natural human motion to allow a robot to adapt to sidewalk navigation in a safe and socially-compliant manner. We developed a group surfing method which aims to imitate the optimal pedestrian group for bringing the robot closer to its goal. For pedestrian-sparse environments, we propose a sidewalk edge detection and following method. Underlying these two navigation methods, the collision avoidance scheme is human-aware. The integrated navigation stack is evaluated and demonstrated in simulation. A hardware demonstration is also presented.
机译:在本文中,我们为行人专用的人行道环境中的移动机器人提出了一种新颖的导航系统。人行道的独特之处在于,行人共享空间既具有道路又具有室内空间的特征。像道路上的车辆一样,行人运动通常表现为相反方向的线性流动。另一方面,行人也很拥挤,可以表现出比车辆更多的随机运动。传统算法不足以确保在行人周围安全导航并留在人行道上。因此,我们的方法利用人类自然运动的优势,允许机器人以安全且符合社会要求的方式适应人行道导航。我们开发了一种群组冲浪方法,旨在模仿最佳步行者群体,以使机器人更接近其目标。对于行人稀少的环境,我们提出了人行道边缘检测和跟踪方法。在这两种导航方法的基础上,防撞方案是可识别人类的。对集成导航堆栈进行评估并在仿真中进行演示。还提供了硬件演示。

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