CAREER: An Unified Approach to Mobile Robot Localization and Navigation

本研究探讨在动态、部分已知的环境中，设计并实现自主多移动机器人定位/导航的框架。该框架将集成自主协作定位和导航能力。特别是，将探索基于自主协作传感器的导航能力，包括基于外推人工势场的路径规划；借助不确定区域计算技术的基于连续感知的定位方法；适用于动态的、部分已知的环境的稳健、安全的分布式控制技术，以便在存在未知或移动障碍的情况下进行高效的在线调整和重新规划。移动机器人具有各种传感器和控制器来通知或采取行动响应环境。能够在数据收集操作之间动态重新配置传感器，从而能够规划传感策略。每个感官动作都会提高对环境的认识；因此，每个感官动作都可以利用比以前的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机械系统的基于传感器的控制。该方法将是实际机器设计和实施方面的突破。拟议的协作、分布式、健壮和廉价的多个移动机器人将被用于许多潜在的应用，从机械机械的维护和维修，到清理事故、搜救行动，或者帮助家庭中的残疾人或老年人。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，重点是机器人学和机电一体化，并让本科生参与研究。它还包括帮助高中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，通过德克萨斯BEST机器人竞赛计划为学生提供鼓励抽象思维、自我指导学习和决策的学术体验。

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.