NRI: Small: A Co-Robotic Navigation Aid for the Visually Impaired

NRI：小型：为视障人士提供协作机器人导航辅助设备

• 批准号: 8704450
• 负责人: Cang Ye
• 金额: $ 10.34万
• 依托单位: UNIVERSITY OF ARKANSAS AT LITTLE ROCK
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-01 至 2016-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8704450
• 关键词: Address; Canes; Communities; Computer Vision Systems; Detection; Development; Devices; Engineering; Environment; Future; Healthcare; High School Student; Human; Law Enforcement; Methods; Military Personnel; Mission; Modeling; National Institute of Biomedical Imaging and Bioengineering; Pattern Recognition; Positioning Attribute; Public Health; Quality of life; Recruitment Activity; Rehabilitation therapy; Research; Research Infrastructure; Robot; Robotics; Science; Solutions; Structure; Students; Technology; Time; Training; Travel; Universities; Visual; Visual impairment; base; blind; career; graduate student; improved; innovation; navigation aid; object recognition; programs; public health relevance; rehabilitation engineering; robotic device; undergraduate student; way finding

DESCRIPTION (provided by applicant): The project's objective is to develop enabling technology for a co-robotic navigation aid, called a Co-Robotic Cane (CRC), for the visually impaired. The CRC is able to collaborate with its user via intuitive Human-Device Interaction (HDl) mechanisms for effective navigation in 3D environments. The CRCs navigational functions include device position estimation, wayfinding, obstacle detection/avoidance, and object recognition. The use of the CRC will improve the visually impaired's independent mobility and thus their quality of life. The proposal's educational plan is to involve graduate, undergraduate and high school students in the project, and use the project's activities to recruit and retain engineering students. The proposal's Intellectual Merit is the development of new computer vision methods that support accurate blind navigation in 3D environments and intuitive HDl interfaces for effective use of device. These methods include: (1) a new robotic pose estimation method that provides accurate device pose by integrating egomotion estimation and visual feature tracking; (2) a pattern recognition method based on the Gaussian Mixture Model that may recognize indoor structures and objects for wayfinding and obstacle manipulation/ avoidance; (3) an innovative mechanism for intuitive conveying of the desired travel direction; and (4) a human intent detection interface for automatic device mode switching. The GPU implementation of the computer vision methods will make real-time execution possible. The proposed blind navigation solution will endow the CRC with advanced navigational functions that are currently unavailable in the existing blind navigation aids. The PI's team has performed proof of concept studies for the computer vision methods and the results are promising. The broader impacts include: (1) the methods' near term applications will impact the large visually impaired community; (2) the methods will improve the autonomy of small robots and portable robotic devices that have a myriad of applications in military surveillance, law enforcement, and search and rescue; and (3) the project will improve the research infrastructure of the Pi's university and train graduate and undergraduate students for their future careers in science and engineering.

描述（由申请人提供）：该项目的目标是为视力障碍的共同动物导航辅助辅助开发启用技术，称为共生甘蔗（CRC）。 CRC能够通过直观的人机互动（HDL）机制与其用户合作，以​​在3D环境中有效导航。 CRCS导航功能包括设备位置估计，寻路，障碍检测/避免和对象识别。 CRC的使用将改善视力障碍的独立移动性，从而改善其生活质量。该提案的教育计划是让研究生，本科和高中生参与该项目，并利用该项目的活动来招募和保留工程专业的学生。该提案的智力优点是开发新的计算机视觉方法，这些方法支持3D环境中准确的盲目导航以及直观的HDL接口，以有效使用设备。这些方法包括：（1）一种新的机器人姿势估计方法，该方法通过整合eGomotion估计和视觉特征跟踪来提供精确的设备姿势； （2）一种基于高斯混合模型的模式识别方法，该方法可能会识别室内结构和物体，以进行寻路和障碍物操纵/避免； （3）直观传达所需旅行方向的创新机制； （4）自动设备模式切换的人类意图检测接口。计算机视觉方法的GPU实现将使实时执行成为可能。拟议的盲型导航解决方案将赋予CRC的高级导航功能，这些功能目前在现有的盲目导航辅助工具中无法使用。 PI的团队已经为计算机视觉方法进行了概念研究证明，结果很有希望。更广泛的影响包括：（1）方法的近期应用将影响大型视力障碍社区； （2）这些方法将提高小型机器人和便携式机器人设备的自主权，这些机器人在军事监视，执法和搜查中都有无数应用； （3）该项目将改善PI大学的研究基础设施，并为他们在科学和工程领域的未来职业而培训毕业生和本科生。