Robot motion planning: multi-sensory uncertainty fields enhanced with obstacle avoidance
Robot motion planning: multi-sensory uncertainty fields enhanced with obstacle avoidance
复制标题
机器人运动规划：通过避障增强多感官不确定性场
DOI：
10.1109/iros.1996.568963
复制
发表时间：
1996
期刊：
影响因子：
--
通讯作者：
Yiannis Komninos
中科院分区：
文献类型：
--
作者：
P. Trahanias;Yiannis Komninos
机器人运动规划是接近本文通过估计其配置的不确定性，由机器人传感器计算。由于移动的机器人平台通常配备有各种范围传感器，因此从所有传感器返回的测量值用于上述估计。最近提出的感官不确定性领域（SUFs）的概念，正在扩展到包括所有可用的外部感官数据源。多传感器不确定性场（MSUF）的引入，从而导致更准确的配置估计。此外，为了应付意外的对象（障碍物）在执行时遇到的，导航算法增强了避障和导航恢复技术。多个传感器和避障的引入有助于在室内环境和存在意外物体的情况下进行准确导航。这是证明了从该方法的实施获得的导航结果。
Robot motion planning is being approached in this paper by estimating the uncertainty of its configuration that is computed by the robot sensors. Since mobile robotic platforms are usually equipped with a variety of range sensors, measurements returned from all sensors are employed for the above estimation. The notion of sensory uncertainty fields (SUFs), recently proposed, is being extended to incorporate all the available sources of external sensory data. The multisensory uncertainty field (MSUF) is introduced which results in more accurate configuration estimation. Moreover, in order to cope with unexpected objects (obstacles) encountered at execution time, the navigation algorithm is augmented with an obstacle avoidance and navigation resuming technique. The introduction of multiple sensors and obstacle avoidance facilitates accurate navigation in indoor environments and in the presence of unexpected objects. This is demonstrated by navigation results obtained from an implementation of this method.