Towards more Natural, Intelligent, and Effective Robotic Grasp and Manipulations

实现更自然、智能、有效的机器人抓取和操作

• 批准号: RGPIN-2018-06253
• 负责人: RajiKermani, Mehrdad
• 金额: $ 2.33万
• 依托单位: University of Western Ontario
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=714166
• 关键词: Towards; more; Natural; Intelligent; Effective

To date, in controlled and accurately modeled environments such as factory floors, robots grasp massive objects and carry them with blurring speed and unerring precision. But, outside of such settings and in natural environment, every day manipulation tasks that we take for granted-even as simple as fetching a pen-can stump the most sophisticated robots. As robots increasingly make their way into functional roles in everyday human environments, we need them to be able to interact and work effectively with, for, and around people. The long-term vision of this research is to develop new and innovative solutions to empower robots to interact, through grasping, with their environment and humans more naturally, with speeds, dexterities, and degrees of autonomy that are comparable to their human counterparts. This vision is motivated by enormous practical values. At the same time, it entails difficult challenges related to the design, formulation of the grasp (grasp planning), maintaining the grasp and manipulating objects (grasp control), and the intersection of these topics with cognitive and functional structure of human grasping. By addressing some of these challenges through carefully selected short-term objectives, the proposed research program promises to deliver new solutions that pave the path towards enabling its long-term goal. Objective 1 focuses on the formulation of new Grasp Quality (GQ) measures applicable to a wider range of grasps. The formulation of GQ measures is an important open problem. A GQ measure is the main tool used for the entire process of grasp planning, grasp evaluating, and grasp control. Objective 2 focuses on developing new theoretical tools and enabling technologies to include active compliance (similar to human's muscle stiffening) in grasping. The new formulation based on active compliance will lead to more natural and robust grasp using algorithms that are substantially more powerful than passive approaches. Objective 3 develops new control algorithms that treat the control of the arm and the control of the hand as a unified problem, allowing for better coordination of the hand and arm and avoiding otherwise sub-optimal and unfeasible solutions. An important part of the proposed research program is the training of highly qualified personnel (HQP) both at graduate and undergraduate levels. The training received by the HQPs will provide them with in-depth knowledge and specialized expertise that ultimately lead to their competitive advantage in today's job market and their future professional success. By addressing important open problems in robotic grasping, the proposed research program will produce quality publications and other measurable impacts that are important to the Canadian robotic industry at large.

到目前为止，在工厂车间等受控和精确建模的环境中，机器人可以抓取巨大的物体，并以模糊的速度和无误的精度携带它们。但是，在这样的环境和自然环境下，我们认为理所当然的日常操作任务--甚至像拿笔这样简单--可能会难倒最复杂的机器人。随着机器人越来越多地成为日常人类环境中的功能角色，我们需要它们能够与人、为人和周围的人有效地互动和工作。 这项研究的长期愿景是开发新的创新解决方案，使机器人能够通过抓取与环境和人类更自然地互动，速度、灵活性和自主性可与人类同行相媲美。这一愿景是由巨大的实用价值推动的。同时，在抓取的设计、制定(抓取规划)、保持抓取和操纵对象(抓取控制)以及这些主题与人类抓取的认知结构和功能结构的交集等方面也面临着困难的挑战。通过精心选择的短期目标来应对其中的一些挑战，拟议的研究计划承诺提供新的解决方案，为实现其长期目标铺平道路。 目标1重点是制定适用于更广泛的抓握的新的抓握质量(GQ)措施。GQ措施的制定是一个重要的开放问题。GQ测量是抓紧规划、抓紧评价、抓紧控制全过程的主要工具。 目标2侧重于开发新的理论工具和使技术能够在握力中包括主动顺应性(类似于人类的肌肉僵硬)。基于主动合规的新公式将使用比被动方法强大得多的算法来实现更自然和更健壮的掌握。 目标3开发了新的控制算法，将手臂的控制和手的控制作为一个统一的问题来处理，允许更好地协调手和手臂，避免否则次优和不可行解。 拟议的研究计划的一个重要部分是培养高素质的研究生和本科生人才。HQP所接受的培训将为他们提供深入的知识和专门知识，最终导致他们在今天的就业市场上获得竞争优势，并在未来取得职业成功。通过解决机器人抓取中的重要公开问题，拟议的研究计划将产生高质量的出版物和其他可测量的影响，这些对整个加拿大机器人行业非常重要。