论文标题
在与人类共享的环境中导航的移动机器人的安全运动计划
Safe Motion Planning for a Mobile Robot Navigating in Environments Shared with Humans
论文作者
论文摘要
在本文中，考虑了与人共享环境的机器人，并且可以在$ \ text {rrt}^\ text {x} $中利用的成本函数，这是一种基于随机抽样的基于随机抽样的算法，可以保证渐近最佳性，以允许进行安全运动。成本函数是基于使用线性随机模型进行的人类运动预测的危险指数加权的路径长度，假设在人类轨迹的实验数据集中计算出恒定的纵向速度和不同的横向速度以及基于GMM/GMR的模型。使用在现实世界中收集的人类轨迹的数据集对所提出的方法进行了验证。
In this paper, a robot navigating an environment shared with humans is considered, and a cost function that can be exploited in $\text{RRT}^\text{X}$, a randomized sampling-based replanning algorithm that guarantees asymptotic optimality, to allow for a safe motion is proposed. The cost function is a path length weighted by a danger index based on a prediction of human motion performed using either a linear stochastic model, assuming constant longitudinal velocity and varying lateral velocity, and a GMM/GMR-based model, computed on an experimental dataset of human trajectories. The proposed approach is validated using a dataset of human trajectories collected in a real world setting.
