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: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=662936
• 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，在受控和精确建模的环境中，如工厂车间，机器人可以抓取大量物体，并以模糊的速度和准确的精度搬运它们。但是，在这样的环境之外，在自然环境中，我们认为理所当然的日常操作任务即使是像取笔这样简单的任务也可以难倒最复杂的机器人。随着机器人越来越多地在日常人类环境中发挥作用，我们需要它们能够与人互动并有效地工作，为人工作，并在周围工作。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更自然地与环境和人类互动，速度，灵巧性和自主程度与人类相当。这一愿景的动机是巨大的实际价值。与此同时，它带来了困难的挑战，有关的设计，制定的把握（把握规划），保持把握和操纵对象（把握控制），以及这些主题与人类的认知和功能结构的交叉点把握。通过精心挑选的短期目标来应对其中一些挑战，拟议的研究计划有望提供新的解决方案，为实现其长期目标铺平道路。目标1侧重于制定适用于更广泛抓握的新抓握质量（GQ）措施。GQ测度的制定是一个重要的开放问题。GQ测量是用于抓取规划、抓取评估和抓取控制的整个过程的主要工具。目标2的重点是开发新的理论工具和技术，包括主动顺应性（类似于人类的肌肉硬化）在抓。基于主动顺应性的新公式将使用比被动方法更强大的算法来实现更自然和更强大的抓握。*目标3：开发新的控制算法，将手臂的控制和手的控制作为一个统一的问题来处理，从而使手和手臂更好地协调，避免出现次优和不可行的解决方案。拟议的研究计划的一个重要组成部分是高素质人才（HQP）在研究生和本科水平的培训。HQP接受的培训将为他们提供深入的知识和专业知识，最终导致他们在当今就业市场的竞争优势和未来的职业成功。通过解决机器人抓取中的重要开放问题，拟议的研究计划将产生高质量的出版物和其他可衡量的影响，这些影响对整个加拿大机器人行业都很重要。