Safe Task Planning Integrating Uncertainties and Local Maps Federations
Safe Task Planning Integrating Uncertainties and Local Maps Federations
复制标题
集成不确定性和本地地图联合的安全任务规划
DOI：
10.1177/027836490001900604
复制
发表时间：
2000
期刊：
影响因子：
--
通讯作者：
N. L. Fort
中科院分区：
文献类型：
--
作者：
A. Lambert;N. L. Fort
研究了室内地图环境下非完整移动机器人位移任务的安全任务生成问题。这项研究的目标是计划安全的动作(路径跟踪)和观察(我们称之为局部地图联盟[LMF])，将机器人引导到可以感知相关特征的位置，从而实现相对于其环境的最佳定位。提出了一种处理不确定性的路径规划方法，该方法同时管理了非完整移动机器人定位和控制中的不确定性。地图不确定性是使用本地地图概念来处理的，本地地图概念是作为一组用于规划和执行健壮运动的最佳地标引入的。该方法的安全性在于规划阶段和导航阶段的混合。
This paper deals with the generation of safe tasks for displacement missions of a nonholonomic mobile robot in a mapped indoor environment. The goal of this study is to plan safe actions (path-following) as well as observations (we call it local maps federation [LMF]), leading the robot to configurations where pertinent features can be sensed, thus attaining best localization relative to its environment. A path-planning method dealing with uncertainties is proposed, where both uncertainties in localization and in control of a nonholonomic mobile robot are managed. Maps uncertainties are handled using the local map concept, which is introduced as a set of the best landmarks used for planning and executing robust motion movements. The safeness of the proposed method is due to the mixing between the planning phase and the navigation phase.