Capturing and Presenting Route Descriptions for People with Vision Loss

描述（由申请人提供）： 拟议的研究的目的是增加独立导航的室内空间，特别是不熟悉的室内空间的视觉障碍的人的容易性。目前，如果不向视力正常的人寻求帮助，就无法做到这一点。此外，调查人员希望确定在不安装特殊建筑基础设施（例如，谈话标志），并要求人们携带专门为此目的和仅为这一人群设计的特殊技术。为此，调查人员希望探索一种新的模式，即建立信息数据库，以满足这一人群的特定方向和寻路需求。这些数据库将为每个可检测的建筑物特征分配地理意义，将每个可检测的特征视为面包屑，可以用来标记通往选定目的地的路线。此外，该建筑物数据库将包含描述每个建筑物空间的可达性的信息，以便可以绘制和遵循通往选定目的地的最易达和最容易穿越的路线。 为了测试这种新模式的可行性，有三个具体目标：（1）可检测类型的建筑特征将被定义并与该人群的需求和多样性相匹配，（2）使用机器人助手开发捕获和组织该建筑数据的一致且准确的方法，以及（3）使用这种新系统的参与者的导航性能将被评估。为了实现第一个目标，将招募代表人口多样性的60名参与者，并要求他们在各种测试环境中描述哪些特征是可检测的和对他们有意义的。将根据与参与者技能和功能性剩余视力水平相关的自然发生的数据分组来组织所得数据库。然后将根据这些数据分组制定一个数据列报模式，以便向每个人提供的信息与他们有效使用信息的能力相匹配。例如，视觉提示将不会提供给没有光感的人，盲文相关信息将不会提供给不会阅读盲文的人。 第二个目标将使用一个机器人助手来实现，该助手将被编程为半自动建筑测量员助手。这个机器人是在格鲁吉亚科技医疗机器人实验室（HRL）开发的，作为身体残疾人士的助手，旨在由行动不便的人远程驾驶通过建筑空间。它采用了光探测和测距（LIDAR）系统，该系统可以生成它所驾驶的空间的2D和3D渲染，并有一个摄像头来捕捉设置的图像。测量员将在台式计算机上处理和整理收集的数据。 第三个目标-建筑信息系统的评估-将雇用30名代表人口多样性的参与者来完成。在平衡交叉试验中，使用开发的数据库的参与者表现将与定向和移动性（O&M）教练充分培训人员如何最好地导航该建筑环境的表现进行比较。 假设如下：假设1 -如果对视障人群导入的用于导航的建筑物数据被定制以将数据总量减少到仅与每个人的实际需求相关的数据量（即，他们的技能水平、视觉功能、触觉功能等）;那么在熟悉的路线中，将产生接近于该路线的性能，而独立性能在以前不太可能成功。} {假设2 -当开发的格鲁吉亚科技HRL机器人被O&M专家用于编译视障人群的输入建筑数据以用于导航时，结果（收集的数据）将在各种建筑设置中是可重复的、可靠的和一致的，如在重测试验中所指示的。}

DESCRIPTION (provided by applicant): The purpose of the proposed research is to increase the ease of independently navigating indoor spaces-in particular unfamiliar indoor spaces-for persons with a visual impairment. Currently this cannot be done without asking a sighted person for assistance. Further, the investigators want to determine the extent to which this might be done without installing a special building infrastructure (e.g., Talking Signs) and requiring persons to carry special technologies designed just for this purpose and only for this population. To this end the investigators wish to explore a new paradigm whereby building information databases would be implemented to meet the specific orientation and wayfinding needs of this population. These databases would assign geographic meaning to every detectable building feature, treating each detectable feature as a bread crumb that can be used to mark the route to a selected destination. In addition, this building database will contain information describing the accessibility of each building space so that the most accessible and easily traversed route to a selected destination can be plotted and followed. To test the feasibility of this new paradigm, there are three specific aims: (1) detectable types of building features will be defined and matched to the needs and diversity of this population, (2) a consistent and accurate means of capturing and organizing this building data will be developed using a robotic assistant, and (3) navigation performance of participants using this new system will be evaluated. To accomplish the First aim, 60 participants representing the diversity of the population will be recruited and asked to describe, across a variety of test settings, what features are detectable and meaningful to them. The resulting database will be organized according to naturally-occurring data groupings associated with participant skills and level of functional residual vision. A data presentation schema based on these data groupings will then be developed, so that the information provided each person matches their ability to use it effectively. For instance, visual cues would not be provided to persons with no light perception, and Braille-related information would not be provided to persons who do not read Braille. The second aim will be accomplished using a robot assistant that will be programmed to work as a semi-automated building surveyor assistant. This robot, developed at the Georgia Tech Healthcare Robotics Lab (HRL) as an assistant for persons with physical disabilities, was designed to be remotely driven through building spaces by a person with limited mobility. It employs a Light Detection and Ranging (LIDAR) system that produces 2D and 3D renderings of the spaces it is driven through and has a camera to capture images of the settings. Collected data will be processed and organized on a desktop computer by the surveyor. The third aim-evaluation of the building information system-will be accomplished employing 30 participants representing the diversity of the population. In counter-balanced cross-over trials participant performance using the developed database will be compared with performance where an Orientation and Mobility (O&M) instructor has fully trained the person how best to navigate that building environment. The hypotheses are as follows: {Hypothesis 1 - If building data of import to a visually impaired population for navigtion is customized to reduce the total amount of data to just that which is relevant to each person's actual needs (i.e., their level of skill, visual function, tactile function, etc.); then performance approaching that in a familiar route will result, where independent performance was previously unlikely to be successful.} {Hypothesis 2 - When the developed Georgia Tech HRL robot is used by an O&M expert to compile building data of import to a visually impaired population for navigation, the results (data collected) will be repeatable, reliable and consistent across a variety of building settings as indicated in test-retest trials.}