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)很高兴在一个为期三年的自主水下机器人研究计划中进行合作。使用遥控系留水下航行器在近海和海洋情况下例行执行关键的水下任务清楚地表明了这些系统的效用和重要性。自动机器人和机器人技术的最新发展现在为预测水下机器人和机器人的能力有可能大幅扩展奠定了基础。涉及的技术范围很广，包括传感器、控制、电源、计算、体系结构和数据表示。协调研究计划将重点放在基于地图的知识表示上，以直接解决自主水下机器人的几个核心问题。我们将开发方法来建立、存储和使用自动驾驶车辆执行有用任务所需的知识。具体地说，我们将开发“带注释的地图”，它为地图中特定对象和位置的信息编制索引。注释可用于多种目的：描述对象、提供感知或控制的提示，或指定要采取的特定操作。我们将提供一种查询机制，以根据注释的地图位置检索注释。我们还将构建“触发器”，当车辆到达地图中的给定位置时，它将使指定的消息传递到特定的进程。这些带注释的地图将在支持目前自主系统无法执行的任务方面发挥关键作用。

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.