ActivATOR - Active AudiTiOn for Robots

ActivATOR - 机器人主动审核

• 批准号: EP/W017466/1
• 负责人: Christine Evers
• 金额: $ 56.48万
• 依托单位: University of Southampton
• 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
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FW017466%2F1
• 关键词: ActivATOR; Active; AudiTiOn; Robots

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.

声音中的生命发生在运动中。作为人类的倾听者，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，以便更好地听到（例如，通过接近感兴趣的声源），以识别对象（例如，通过触摸物体并收听产生的声音），以检测故障（例如，通过移动物体来聆听异常的吱吱声），并释放思想（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）的基本先决条件。该项目将开创主动机器人听觉的基础，概率框架，使具体代理控制自己的身体运动（'自我运动'）在现实的听觉注意，声学环境（家庭，公共空间和涉及多个竞争声源的环境）。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后果。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，以超越人体的限制（感官准确性，力量，耐力，记忆）。因此，拟议的研究有可能改变和破坏涉及机器听力的一系列行业，从人机增强（智能假肢，辅助听力技术，脑机接口）到人机协作（行星探索，搜索和救援，危险材料清除）和自动化（环境监测，自动驾驶汽车，医疗保健中的人工智能辅助诊断）。这个项目将考虑一个协作机器人（“cobot”）的具体案例研究，增强听觉障碍的人类合作伙伴的听觉体验。听力损失是英国第二大最常见的残疾，影响着1100万人。听力损失会影响情境意识和沟通能力，这会影响心理健康，在极端情况下还会影响认知功能。然而，由于各种复杂的原因，从不适到社会耻辱，只有200万人选择佩戴助听器。该项目的目标是开发一种协作机器人，以增强听力受损者的听觉体验。协作机器人将在人类伴侣的家中自主移动，以协助日常工作。我们的研究将使协作机器人能够利用自我运动来学习声学场景的内部表示（孩子们喋喋不休，水壶沸腾，配偶呼救）。协作机器人将通过个人智能设备（手表、移动的电话）与合作伙伴进行交互。使用人机交互界面，协作机器人将通过振动消息提醒其合作伙伴显著事件（呼叫帮助），并通过交互式地图共享其听觉体验，该交互式地图可视化听觉线索并指示显著性（例如，与智能设备相比，协作机器人将具有主动关注和探索不确定事件（砰的一声上楼）并采取行动（帮助配偶、呼叫救护车）的独特能力，而不需要在个人空间（浴室、卧室）中永久安装设备。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。