[概述]移动机器人自主探索
Autonomous Exploration自主探索
移动机器人自主探索最主要的任务是确定机器人下一步的期望运动位置，最终实现全局范围内以最短无碰撞路径获取最多未知正确环境信息。
Autonomous Navigation自主导航
自主导航和自主探索都涉及两个问题：一个是自身定位和环境地图构建（SLAM），一个是路径规划（Path Planing）。后者包括全局路径规划和局部避障（Obstacle Avoidance）。区别于自主导航，自主探索不包含明确的目标点（Goals），根据已知区域探索未知区域，需要找到边界条件，优化机器人的行走路径，以最小的代价完成未知环境的探索。
边界探索算法
Yamauchi．B提出了基于边界探索算法(Froniter-Based)该方法基于图像分割技术提取局部栅格地图中已知和未知区域之间的边界，然后控制机器人选择向最近边界区域运动，从而获取新环境信息，扩大地图创建。
NBV（Next best view）探索方法
路径规划技术是机器人研究领域中的一个重要分支。所谓机器人的最优路径规划问题,就是依据某个或某些优化准则(如工作代价最小、行走路线最短、行走时间最短等),在其工作空间中找到一条从起始状态到目标状态的能避开障碍物的最优路径。依据某种最优准则，在工作空间中寻找一条从起始状态到目标状态的避开障碍物的最优路径。需要解决的问题：
1. 始于初始点止于目标点。
2. 避障。
3. 尽可能优化的路径。
（by 王超群）
Virtual Force Fields(VFF) 虚拟力场法 （Artificial potential field 人工势场法）
Real-Time Obstacle Avoidance for Manipulators and Mobile Robots
http://www-personal.umich.edu/~johannb/vff&vfh.htm
RRT快速搜索随机树
一个浅陋的自主探索的方案
更新一下：
ROS中的导航包
先锋机器人P3-AT中的自动导航
ArPathPlanningTask is the navigation component of ARNL. As an asynchronous task (thread) working with the ARIA robot control infrastructure, it's job is to plan the shortest and safest path for and then drive your mobile robot from its current position to any other reachable point in its mapped environment. ArPathPlanningTask navigates to a goal using an ArMap indicating sensable obstacles (walls, furniture, etc.), forbidden lines and areas, goal points, etc. and samples that data into a lower resolution grid. It then searches this grid for cells that are sufficiently far from obstacles to form a clear "global path" for the robot in that grid from the robot's current position to the goal. It then activates an ArAction which drives the robot along that path, and while navigating along this path, ArPathPlanningTask uses a dynamic window method and local replanning to avoid unmapped obstacles.
The path planning task uses a grid based search to compute the shortest and safe path from the present robot pose to any reachable point in the given robot enviroment map. It then enables an action that follows the planned path, all the while using the dynamic window method to avoid unmapped obstacles in its path. The path planning thread requires fairly accurate robot location. Hence a localization task (ArLocalizationTask or ArSonarLocalizationTask) must also be run concurrently with the path planning task.
