ActivATOR - Active AudiTiOn for Robots
ActivATOR - Active AudiTiOn for Robots
批准号:
EP/W017466/1
负责人:
Christine Evers
金额:
$56.48万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
声音中的生命发生在运动中。作为人类的听众,听觉--倾听的能力--是由我们的身体和环境之间的物理相互作用形成的。我们将运动与听觉感知相结合,以便更好地听(例如,通过接近感兴趣的声源)、识别对象(例如,通过触摸对象并收听由此产生的声音)、检测故障(例如,通过移动对象来听异常吱吱声),以及卸载思想(例如,通过敲击表面来回忆音乐片段)。因此,理解和利用运动中的声音的能力是体现人工智能(AI)的基本前提。该项目将是主动机器人试听的基础概率框架的先驱,该框架使具体的代理能够在现实的声学环境(家庭、公共场所和涉及多个相互竞争的声源的环境)中控制其自身身体的运动(“自我运动”)以获得听觉注意力。通过将声音与运动相结合,该项目将使机器能够想象、控制和利用与环境的物理交互的听觉结果。通过改变机器在声音中理解生命的方式,研究成果将对新的新兴市场至关重要,这些市场使机器人能够增强而不是竞争人类,以超越人体的局限性(感觉准确性、力量、耐力、记忆力)。因此,拟议的研究有可能改变和颠覆一系列涉及机器倾听的行业,从人-机器人增强(智能假肢、辅助倾听技术、脑机接口)到人-机器人协作(行星探索、搜救、危险材料清除)和自动化(环境监测、自动驾驶车辆、医疗保健中的人工智能辅助诊断)。这个项目将考虑协作机器人(Cobot)的具体案例研究,该机器人可以增强听力受损人类伴侣的听觉体验。听力损失是英国第二大最常见的残疾,影响了1100万人。听力丧失会影响情境意识和沟通能力,这可能会影响心理健康,在极端情况下还会影响认知功能。然而,由于从不适到社会耻辱等复杂原因,只有200万人选择佩戴助听器。该项目的雄心是开发一种合作机器人,以增强听障人士的听觉体验。Cobot将在人类伴侣的家庭中自主移动,帮助完成日常任务。我们的研究将使Cobot能够利用自我运动来学习声音场景的内部表征(孩子聊天,水壶沸腾,配偶呼救)。Cobot将通过面对面的智能设备(手表、手机)与其合作伙伴进行交互。使用人机交互界面,Cobot将通过振动消息提醒其伙伴显著的事件(呼救),并通过交互式地图分享其听觉体验,这些地图可视化听觉提示,并指示显著程度(例如,响度、自发性)和价位(积极与关切)。与智能设备相比,Cobot将具有独特的能力,可以主动关注和探索不确定的事件(砰的一声上楼),并采取行动(协助配偶,呼叫救护车),而不需要在个人空间(浴室、卧室)永久安装设备。因此,该项目有可能通过实现长期独立生活、保护隐私和促进包容性来改变听力障碍者的生活。
英文摘要
Life in sound occurs in motion. As human listeners, audition - the ability to listen - is shaped by physical interactions between our bodies and the environment. We integrate motion with auditory perception in order to hear better (e.g., by approaching sound sources of interest), to identify objects (e.g., by touching objects and listening to the resulting sound), to detect faults (e.g., by moving objects to listen to anomalous creaks), and to offload thought (e.g., by tapping surfaces to recall musical pieces). Therefore, the ability to make sense of and exploit sounds in motion is a fundamental prerequisite for embodied Artificial Intelligence (AI). This project will pioneer the underpinning, probabilistic framework for active robot audition that enables embodied agents to control the motion of their own bodies ('ego-motion') for auditory attention in realistic, acoustic environments (households, public spaces, and environments involving multiple, competing sound sources).By integrating sound with motion, this project will enable machines to imagine, control and leverage the auditory consequences of physical interactions with the environment. By transforming the ways in which machines make sense of life in sound, the research outcomes will be pivotal for new, emerging markets that enable robots to augment, rather than rival, humans in order to surpass the limitations of the human body (sensory accuracy, strength, endurance, memory). Therefore, the proposed research has the potential to transform and disrupt a whole host of industries involving machine listening, ranging from human-robot augmentation (smart prosthetics, assistive listening technology, brain-computer interfaces) to human-robot collaboration (planetary exploration, search-and-rescue, hazardous material removal) and automation (environmental monitoring, autonomous vehicles, AI-assisted diagnosis in healthcare). This project will consider the specific case study of a collaborative robot ('cobot') that augments the auditory experience of a hearing-impaired human partner. Hearing loss is the second most common disability in the UK, affecting 11M people. The loss of hearing affects situational awareness as well as the ability to communicate, which can impact on mental health and, in extreme cases, cognitive function. Nevertheless, for complex reasons that range from discomfort to social stigma, only 2M people choose to wear hearing aids.The ambition of this project is to develop a cobot that will augment the auditory experience of a hearing-impaired person. The cobot will move autonomously within the human partner's household to assist with everyday tasks. Our research will enable the cobot to exploit ego-motion in order to learn an internal representation of the acoustic scene (children chattering, kettle boiling, spouse calling for help). The cobot will interface with its partner through an on-person smart device (watch, mobile phone). Using the human-cobot interface, the cobot will alert its partner of salient events (call for help) via vibrating messages, and share its auditory experiences via interactive maps that visualise auditory cues and indicate saliency (e.g., loudness, spontaneity) and valence (positive vs concerning).In contrast to smart devices, the cobot will have the unique capability to actively attend to and explore uncertain events (thump upstairs), and take action (assist spouse, call ambulance) without the need for permanently installed devices in personal spaces (bathroom, bedroom). Therefore, the project has the potential to transform the lives of people with hearing impairments by enabling long-term independent living, safeguarding privacy, and fostering inclusivity.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Acoustic Signal Processing and Scene Analysis for Socially Assistive Robots
-
批准号:EP/P001017/1
-
项目类别:Fellowship
-
资助金额:$42.06万
-
财政年份:2017
-
负责人:Christine Evers
-
依托单位:
国内基金
海外基金
光-电驱动下的AIE-active手性高分子CPL液晶器件研究
-
批准号:92156014
-
项目类别:重大研究计划
-
资助金额:70.0万元
-
批准年份:2021
-
负责人:成义祥
-
依托单位:
光-电驱动下的AIE-active手性高分子CPL液晶器件研究
-
批准号:--
-
项目类别:--
-
资助金额:70万元
-
批准年份:2021
-
负责人:成义祥
-
依托单位: