Passenger discomfort map for autonomous navigation in a robotic wheelchair
Passenger discomfort map for autonomous navigation in a robotic wheelchair
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DOI：
10.1016/j.robot.2018.02.002
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发表时间：
2018-05
期刊：
影响因子：
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通讯作者：
Luis Yoichi Morales Saiki;Atsushi Watanabe;Florent Ferreri;J. Even;K. Shinozawa;N. Hagita
中科院分区：
文献类型：
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作者：
Luis Yoichi Morales Saiki;Atsushi Watanabe;Florent Ferreri;J. Even;K. Shinozawa;N. Hagita
这项工作提出了一种考虑人类乘客舒适感的导航方法。舒适是一种轻松自在、没有压力的状态；因此，舒适的导航除了安全之外，还让乘客感觉没有焦虑和压力。本研究考虑如何计算乘客舒适路径。为了计算此类路径，需要研究能见度良好和能见度较低的地点的乘客不适感。在能见度良好的地方，研究了乘客在道路上骑行的偏好。对于具有不可见区域的位置，研究乘客可见度与不适之间的关系。进行自主导航实验是为了构建人类不适感地图，用于计算全局路径。提出了一种路径规划器，可最小化三变量成本函数：位置不舒适成本、区域可见性成本和路径长度成本。规划器参数根据从参与者自动驾驶轨迹中获取的数据构建的复合轨迹直方图进行校准。最后，30 名参与者的自主导航实验表明，所提出的方法比最先进的最短规划器方法更舒适。
This work presents a navigational approach that takes into consideration the perception of comfort by a human passenger. Comfort is the state of being at ease and free from stress; thus, comfortable navigation is a ride that, in addition to being safe, is perceived by the passenger as being free from anxiety and stress. This study considers how to compute passenger comfortable paths. To compute such paths, passenger discomfort is studied in locations with good visibility and those with no visibility. In locations with good visibility, passenger preference to ride in the road is studied. For locations with non-visible areas, the relationship between passenger visibility and discomfort is studied. Autonomous-navigation experiments are performed to build a map of human discomfort that is used to compute global paths. A path planner is proposed that minimizes a three-variable cost function: location discomfort cost, area visibility cost, and path length cost. Planner parameters are calibrated toward a composite trajectory histogram built with data taken from participant self-driving trajectories. Finally, autonomous navigation experiments with 30 participants show that the proposed approach is rated as more comfortable than the state-of-the-art shortest planner approach.