Open Arms is a novel open-source platform of realistic human-like robotic hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the capabilities and accessibility of humanoid robotic grasping and manipulation. The Open Arms framework includes an open SDK and development environment, simulation tools, and application development tools to build and operate Open Arms. This paper describes these hands controls, sensing, mechanisms, aesthetic design, and manufacturing and their real-world applications with a teleoperated nursing robot. From 2015 to 2022, we have designed and established the manufacturing of Open Arms as a low-cost, high functionality robotic arms hardware and software framework to serve both humanoid robot applications and the urgent demand for low-cost prosthetics. Using the techniques of consumer product manufacturing, we set out to define modular, low-cost techniques for approximating the dexterity and sensitivity of human hands. To demonstrate the dexterity and control of our hands, we present a novel Generative Grasping Residual CNN (GGR-CNN) model that can generate robust antipodal grasps from input images of various objects at real-time speeds (22ms). We achieved state-of-the-art accuracy of 92.4% using our model architecture on a standard Cornell Grasping Dataset, which contains a diverse set of household objects.
翻译:开放武器框架包括开放的SDK和开发环境、模拟工具和应用开发工具,用于建造和操作开放武器。本文描述了这些手控、感测、机制、审美设计、制造及其使用远程操作护理机器人的实际应用。从2015年到2022年,我们设计并建立了开放武器生产,作为低成本高功能机械武器硬件和软件框架,为人类机器人应用和低成本假肢的紧急需求提供服务。我们利用消费产品制造技术,设计了模块化、低成本技术,以适应人类手的灵敏度和灵敏度。为了展示我们手的灵巧度和控制,我们展示了新型的General Graspingal NCNN(GGR-CNN)模型,该模型能够从实时计算机机器人应用的各种物体输入图像中产生强力的抗毒针卡。我们用创式的系统(22m)标准型计算机系统(22m),我们已建立一套标准家庭型号(22m)系统。