Advanced Sensor Fusion for Visual Inertial Odometry in Dynamic Indoor Environments

用于动态室内环境中视觉惯性里程计的先进传感器融合

• 批准号: 521664-2017
• 负责人: Ngo, TrungDung
• 金额: $ 1.82万
• 依托单位: University of Prince Edward Island
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=639299
• 关键词: Advanced; Sensor; Fusion; Visual; Inertial

Industrial robots have set important milestones in the era of automated manufacturing by carrying outdangerous and repeatable tasks in the place of humans for over half a century. In this century, professional andmobile service robots are going to play the key role as human counterparts and caregivers in both industrial anddaily-life setting. Similar to industrial robots, mobile service robots will take on the dangerous and dull aspectsof service tasks, freeing time and cognitive demand on human service worker, allowing the worker to makebetter choices in high level decision making and planning. In the context of indoor mobile service robots, as aprerequisite for performing a specific task, the robot must know how to locate itself and a target object. As aresult, the robot must be equipped with a navigation system that is capable of dealing with uncertainties insocial environments. Though foundation techniques exist, very few are found to be adequate in meetingmodern demands. Hence, the scope of this research project is to produce the next generation visual inertialodometry for robot navigation systems in dynamic indoor environments.

半个多世纪以来，工业机器人代替人类执行危险和可重复的任务，在自动化制造时代树立了重要的里程碑。在本世纪，专业和移动服务机器人将在工业和日常生活中扮演人类同行和照顾者的关键角色。与工业机器人类似，移动服务机器人将承担危险和枯燥的服务任务，解放人类服务人员的时间和认知需求，使他们能够在高层决策和规划中做出更好的选择。在室内移动服务机器人的环境中，作为执行特定任务的先决条件，机器人必须知道如何定位自己和目标对象。因此，机器人必须配备一个能够处理社会环境中的不确定性的导航系统。尽管地基技术已经存在，但很少有人被发现足以满足现代需求。因此，本研究项目的研究范围是为动态室内环境中的机器人导航系统开发下一代视觉惯性里程计。