Co-design of feedback control and soft morphology for in-hand manipulation

用于手动操作的反馈控制和软形态的协同设计

• 批准号: 405033880
• 负责人: Professor Dr. Oliver Brock
• 金额: --
• 依托单位: Fachgebiet Robotics and Biology Laboratory
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/405033880?language=en
• 关键词: Co; design; feedback; control; soft

Soft material robotics offers important advantages over over traditional, "hard" robotics. The behavior of a soft robot is not exclusively the result of control commands, as is the case for hard robots. Instead, behavior is also determined by the robot's shape and material properties, i.e. the robot's morphology. As a soft robots come into contact with their environment, they deform, implicitly performing aspects of control, sensing, and actuation. Clever morphological design therefore favorably affects the robot's behavior while at the same time simplifying control and sensing. The benefits of appropriate morphological design have been demonstrated in many systems and applications, ranging from swimming robots to flying robots and from grasping to locomotion.The "programming" of soft robots, however, remains largely an open problem. Whereas for hard robots, programming meant the specification of actuation commands, in the case of soft robots we must program control as well as "program" the robot's morphology to fully leverage the advantages afforded by soft material robotics. And, of course, these two problems interact very closely. We therefore speak of a co-design problem: we must determine control and morphology together to determine the behavior of a system. Existing solutions to this problem consist of solution instances designed by intuition and trial-and-error. For soft material robotics to mature as a field, we must develop an understanding of this novel design process and derive design guidelines that transfer between problems.In this proposal, we will map the design space of feedback control and morphological design in the context of in-hand manipulation. Successful in-hand manipulation requires many contact points between hand and object, leading to significant demands on control, sensing, and morphology. We will therefore be able to address many design challenges in a simple experimental setup with immediate and clear performance feedback. Within the domain of in-hand manipulation, we will derive an understanding of the co-design space, we will develop computational tools and hardware components to support the design process, and we will derive generalizable design insights that can transfer to other application of soft material robotics.

软材料机器人相对于传统的“硬”机器人具有重要的优势。软机器人的行为不像硬机器人那样完全是控制命令的结果。相反，行为还取决于机器人的形状和材料属性，即机器人的形态。当软机器人与环境接触时，它们会变形，隐含地执行控制，传感和驱动方面。因此，巧妙的形态设计有利于影响机器人的行为，同时简化控制和传感。从游泳机器人到飞行机器人，从抓取到移动，形态学设计的好处已经在许多系统和应用中得到了证实，但是软体机器人的“编程”问题仍然是一个悬而未决的问题。而对于硬机器人来说，编程意味着驱动命令的规范，在软机器人的情况下，我们必须编程控制以及“编程”机器人的形态，以充分利用软材料机器人所提供的优势。当然，这两个问题是密切相关的。因此，我们谈到了一个协同设计问题：我们必须一起确定控制和形态，以确定系统的行为。现有的解决方案，这个问题的解决方案由直觉和试错设计的实例。对于软材料机器人成熟的领域，我们必须发展这种新的设计过程的理解，并得出设计准则，之间的问题transfer.In本提案中，我们将映射的反馈控制和形态设计的设计空间的背景下，在手操作。 成功的手操纵需要手和物体之间的许多接触点，从而导致对控制、传感和形态的显著要求。因此，我们将能够在一个简单的实验设置中解决许多设计挑战，并提供即时和清晰的性能反馈。在手操纵领域内，我们将获得对协同设计空间的理解，我们将开发计算工具和硬件组件来支持设计过程，我们将获得可推广的设计见解，可以转移到软材料机器人的其他应用。