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A sonar approach to obstacle detection for a vision-based autonomous wheelchair

机译:一种基于声纳的视觉检测自动轮椅障碍物方法

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An advanced prototype Computer Controlled Power Wheelchair Navigation System or CCPWNS has been developed to provide autonomy for highly disabled users, whose mix of disabilities makes it difficult or impossible to control their own power chairs in their homes. The working paradigm is "teach and repeat" a mode of control for typical industrial holonomic robots. Ultrasound sensors, which during subsequent autonomous tracking will be used to detect obstacles, also are active during teaching. Based upon post-processed data collected during this teaching event, elaborate trajectories - which may involve multiple direction changes, pivoting and so on, depending upon the requirements of the typically restricted spaces within which the chair must operate - will later be called upon by the disabled rider. An off-line postprocessor assigns an ultrasound profile to the sequence of poses of any taught trajectory. Use of this profile during tracking obviates most of the inherent problems of using ultrasound to avoid obstacles while retaining the ability to near solid objects, such as when passing through a narrow doorway, where required by the environment and trajectory objectives. The work in this article describes a procedure to obtain consistent maps of sonar boundaries during the teaching process, and a preliminary approach to use this information during the tracking phase. The approach is illustrated by results obtained by using the CCPWNS prototype.
机译:已经开发出先进的原型计算机控制电动轮椅导航系统或CCPWNS,以为高度残疾的用户提供自主权,残疾人的混合使用使他们很难或不可能在家中控制自己的电动轮椅。工作范例是“传授并重复”典型工业完整机器人的控制方式。在随后的自主跟踪过程中,将使用超声波传感器来检测障碍物,该传感器在教学过程中也处于活动状态。根据在此教学活动中收集到的后处理数据,复杂的轨迹-可能涉及多个方向变化,旋转等,具体取决于椅子必须在其中操作的典型受限空间的要求-稍后将由操作员调用。残疾的骑手。离线后处理器将超声轮廓分配给任何示教轨迹的姿势序列。在跟踪过程中使用此配置文件可以避免使用超声避免障碍的大多数固有问题,同时还能保持靠近固体物体的能力,例如当环境和轨迹目标需要通过狭窄的门口时。本文中的工作描述了在教学过程中获取一致声纳边界图的过程,以及在跟踪阶段使用此信息的初步方法。通过使用CCPWNS原型获得的结果说明了该方法。

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