Annotated Maps for Autonomous Underwater Vehicles

佛罗里达大西洋大学（FAU）和卡内基梅隆大学 (CMU)很高兴能在一个为期三年的项目中合作， 自主水下机器人的研究。 远程使用 控制，系留水下航行器， 在近海和海洋情况下的关键水下任务， 清楚地表明了这两个效用和重要性， 系统. 自主车辆和机器人的最新发展 技术现在构成了预测这一重大问题的基础， 扩展水下的能力是可能的， 车辆和机器人。 所涉及的技术是广泛的 测距和包括传感器，控制，电源，计算， 架构和数据表示。 协调研究计划将侧重于基于地图的 知识表示，以直接解决其中几个问题 自主水下航行器的核心问题。 我们将 开发方法来构建，存储和使用知识， 自动驾驶车辆需要执行有用的任务。 具体来说，我们将开发“注释地图”， 地图中的特定对象和位置的信息。 的 注释可以用于各种各样的目的： 描述物体，提供感知或控制的提示， 或指定要采取的特定行动。 核心提供 基于地图检索注释的查询机制 地点 我们还将建立“触发器”，这将导致 当一个特定的消息被传递到一个特定的进程时， 车辆到达地图中的给定位置。 这些注释 地图将发挥关键作用， 目前自治系统无法触及。

Florida Atlantic University (FAU) and Carnegie Mellon University (CMU) are pleased to cooperate in a three-year program of research on autonomous underwater robots. The use of remotely controlled, tethered underwater vehicles to routinely perform critical underwater tasks in offshore and ocean situations has clearly demonstrated both the utility and importance of these systems. Recent developments in autonomous vehicle and robot technology now form the basis for projecting that significant expansions are possible in the capabilities of underwater vehicles and robotics. The technologies involved are wide ranging and include sensors, controls, power, computing, architectures and data representation. The coordinated research program will focus on map-based knowledge representation to directly address several of these central issues of autonomous underwater vehicles. We will develop methods to build, store, and use the knowledge that autonomous vehicles need to execute useful missions. Specifically, we will develop "annotated maps", which index information to particular objects and locations in the map. The annotations can be used for a wide variety of purposes: describing objects, providing hints for perceptions or control, or specifying particular actions to be taken. We will provide a query mechanism to retrieve annotations based on their map locations. We will also build "triggers", which will cause a specified message to be delivered to a particular process when the vehicle reaches a given location in the map. These annotated maps will serve a crucial role in enabling missions that are currently beyond the reach of autonomous systems.