Novel Human-Inspired Stability and Robustness Concepts for Human-Centred Robots and Biomedical Devices

以人为中心的机器人和生物医学设备的新颖的受人启发的稳定性和鲁棒性概念

• 批准号: RGPIN-2022-05162
• 负责人: Mombaur, Katja
• 金额: $ 3.35万
• 依托单位: University of Waterloo
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=765916
• 关键词: Novel; Human; Inspired; Stability; Robustness

Dramatically increased life expectancy is a great achievement for humankind, but comes at a cost and poses a challenge to society that is not yet sufficiently addressed. In 2019, the Canadian Institute for Health Information reported more than 110,000 seniors' falls as cause for hospitalization, these representing a stunning 41% of all injury-related hospitalizations. Progress in assistive technologies in this field is a paramount and urgent challenge for Canadian and global society. Today, lack of fundamental advances in our understanding and ability to model stability and robustness of human motions remains a roadblock effective human-centered robotics design. Motion stability is achieved when the originally planned motion persists, even in the presence of perturbations. Robustness is the property describing the size of the stability regions around this motion. Stability and robustness are not inherent properties of a system, but of a particular motion of a system; they are among the most important properties of human and animal motion. Yet, how humans achieve them, even in fast and dynamic motions, is still far from being well understood. As a result, robots today still fail in stable motions, relying on much simpler heuristic concepts. Or, stability can only be achieved at the cost of such strong and heavy design that the robots pose a threat to humans and other vulnerable environments. The proposed Discovery Grant program aims to develop a base stability ontology through a set of performance indicators, allowing to capture and validate stability and robustness of human movement in terms of mathematical models, and transfer this knowledge into novel and applicable control concepts. No such model exists today. To establish such an ontology, we will collect very extensive motion data, including challenging motions in sports where stability control is pushed to its limits. The basic idea is that we will learn from these extreme situations in humans, for more standard situations in robots. We will validate the criteria and control mechanisms on existing human-centered robotics and biomedical devices, such as a full size humanoid robot, a lower limb exoskeleton and a robotic rollators, all available in our lab. Effective methods for control of perturbed stability in motions are not only needed for effective assistance to seniors, but for a full spectrum of medical applications, e.g. for care for patients with Parkinson's Disease or Cerebral Palsy. And application possibilities span beyond the healthcare sector. Robots enter our daily lives, e.g. as private service robots or cobots in manufacturing environments. For all these applications, stability and robustness is a key success factor, to allow the robots to move or interact with humans. Advances from this program will benefit Canada's AI, biomedical, and robotics industries, and students will become the next generation of innovators in these growing fields.

预期寿命的大幅提高是人类的一项伟大成就，但它也付出了代价，并对社会提出了尚未得到充分解决的挑战。 2019 年，加拿大健康信息研究所报告称，有超过 110,000 名老年人因跌倒而住院，占所有因伤害而住院的人数比例高达 41%，令人震惊。该领域辅助技术的进步是加拿大和全球社会面临的首要且紧迫的挑战。如今，我们对人体运动稳定性和鲁棒性的理解和建模能力缺乏根本性进展，仍然是有效以人为中心的机器人设计的障碍。当最初计划的运动持续存在时，即使存在扰动，也能实现运动稳定性。鲁棒性是描述该运动周围稳定区域大小的属性。稳定性和鲁棒性不是系统的固有属性，而是系统的特定运动的属性；它们是人类和动物运动最重要的特性之一。然而，人类如何实现这些目标，即使是在快速和动态的运动中，仍然远未得到很好的理解。因此，今天的机器人仍然无法实现稳定的运动，依赖于更简单的启发式概念。或者，只有以机器人对人类和其他脆弱环境构成威胁的坚固而沉重的设计为代价才能实现稳定性。 拟议的发现资助计划旨在通过一组性能指标开发基础稳定性本体，从而能够根据数学模型捕获和验证人体运动的稳定性和鲁棒性，并将这些知识转化为新颖且适用的控制概念。今天不存在这样的模型。为了建立这样的本体，我们将收集非常广泛的运动数据，包括稳定性控制达到极限的运动中的挑战性运动。基本思想是，我们将从人类的这些极端情况中学习，为机器人提供更标准的情况。 我们将验证现有的以人为中心的机器人和生物医学设备的标准和控制机制，例如全尺寸人形机器人、下肢外骨骼和机器人助行车，所有这些都可以在我们的实验室中找到。 控制运动扰动稳定性的有效方法不仅需要有效帮助老年人，而且需要全方位的医疗应用，例如：用于护理帕金森病或脑瘫患者。应用的可能性超出了医疗保健领域。机器人进入我们的日常生活，例如作为制造环境中的私人服务机器人或协作机器人。对于所有这些应用，稳定性和稳健性是关键的成功因素，以允许机器人移动或与人类互动。该项目的进展将使加拿大的人工智能、生物医学和机器人行业受益，学生将成为这些不断发展的领域的下一代创新者。