CAREER: An Unified Approach to Mobile Robot Localization and Navigation

职业：移动机器人定位和导航的统一方法

• 批准号: 0238185
• 负责人: Sooyong Lee
• 金额: $ 41.5万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-03-01 至 2004-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0238185&HistoricalAwards=false
• 关键词: CAREER; Unified; Approach; Mobile; Robot

This research investigates design and implement a framework for autonomous multiple mobile robots localization/navigation in a dynamic, partially known environment. The framework will integrate autonomous cooperative localization and navigation capabilities.In particular, autonomous cooperative sensor-based navigation capabilities will be explored, which integrate; extrapolated artificial potential field based path planning; consecutive sensing based localization methods with the aid of techniques for computing uncertainty regions; robust, safe techniques for distributive control suitable for dynamic, partially known environments that facilitate efficient, on-line adjustment and re-planning in the presence of unknown or moving obstacles.The mobile robots have variety of sensors and controllers to inform or take action in response to the environment. The ability to reconfigure sensors dynamically between data collection operations enables planning of sensing strategies. Each sensory action will improve knowledge of the environment; hence, each sensory action can be chosen utilizing a larger knowledge base than was available for previous actions. An immediate benefit from this work will be a direct use in sensor based control of mechanical systems. The approach will be a breakthrough in practical machine design and implementation.The proposed cooperative, distributive, robust, and inexpensive multiple mobile robots will be used to many potential applications ranging from maintenance and repair of mechanical machinery, to clean up operations for accidents, to search and rescue operations, or to assisting the disabled or elderly around the home.The project's education component focuses on developing new interdisciplinary undergraduate and graduate courses with an emphasis on robotics and mechatronics and involving undergraduate students in research. It also includes helping high school students understand technical concepts and principles, and providing students with a real-world engineering challenge offering students an academic experience that encourages abstract thought, self-directed learning, and decision-making through TexasBEST robot competition program.

本研究探讨设计与实作一个架构，让多个自主式移动的机器人在动态且部分已知的环境中定位/导航。 该框架将集成自主合作定位和导航能力，特别是自主合作的基于传感器的导航能力将被探索，它集成了：基于外推人工势场的路径规划，基于连续传感的定位方法与计算不确定区域的技术的帮助，适用于动态的、部分已知的环境的分布式控制的鲁棒的、安全的技术，在未知或移动障碍物存在的情况下进行在线调整和重新规划。移动的机器人具有各种传感器和控制器，以通知或响应于环境采取行动。 在数据收集操作之间动态地重新配置传感器的能力使得能够规划感测策略。每一个感官动作都将提高对环境的认识;因此，每一个感官动作都可以利用比先前动作更大的知识库来选择。这项工作的直接好处将是直接用于基于传感器的机械系统控制。 该方法将成为实用机器设计和实施的突破。拟议的协作、分布式、鲁棒且廉价的多个移动的机器人将用于许多潜在应用，包括机械机械的维护和维修、事故清理作业、搜救作业、该项目的教育部分侧重于开发新的跨学科本科和研究生课程，重点是机器人和机电一体化，本科生从事研究。 它还包括帮助高中学生理解技术概念和原理，并为学生提供现实世界的工程挑战，为学生提供学术经验，鼓励抽象思维，自主学习和决策，通过德克萨斯州最佳机器人竞赛计划。