Superhuman place recognition with a unified model of human visual processing and rodent spatial memory

具有人类视觉处理和啮齿动物空间记忆统一模型的超人类地点识别

• 批准号: FT140101229
• 负责人: Prof Michael Milford
• 金额: $ 46.15万
• 依托单位: Queensland University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: ARC Future Fellowships
• 财政年份: 2015
• 资助国家: 澳大利亚
• 起止时间: 2015-06-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/FT140101229
• 关键词: Superhuman; place; recognition; unified; model

Current robotic and personal navigation systems leave much to be desired; GPS only works in open outdoor areas, lasers are expensive and cameras are highly sensitive to changing environmental conditions. In contrast, nature has evolved superb navigation systems. This project aims to solve the challenging problem of place recognition, a key component of navigation, by modelling the visual recognition skills of humans and the rodent spatial memory system. This project looks to combine the best understood and most capable components of place recognition in nature to create a whole more capable than its parts, produce advances in robotic and personal navigation technology and lead to breakthroughs in understandings of the brain.

目前的机器人和个人导航系统还有很多需要改进的地方; GPS只在户外开放区域工作，激光器价格昂贵，摄像头对不断变化的环境条件高度敏感。相比之下，大自然进化出了高超的导航系统。该项目旨在通过模拟人类的视觉识别技能和啮齿动物的空间记忆系统，解决具有挑战性的位置识别问题，这是导航的关键组成部分。该项目旨在将自然界中最好理解和最有能力的位置识别组件联合收割机结合起来，创造一个比其部分更有能力的整体，在机器人和个人导航技术方面取得进步，并在对大脑的理解方面取得突破。