SBIR Phase I: Haptic Robotics for Kitting Powertrain Components

这个小企业创新研究（SBIR）第一阶段项目提出，触觉机器人为目前需要人类工人的捡垃圾桶和打包等常见任务提供了有效和有吸引力的解决方案。一个流行的应用领域是对工业机器人进行编程，使其与特定的动力总成部件一起工作。问题：拾取垃圾箱的机器人只能在结构或半结构配置中操作具有简单几何形状的坚固部件；机器视觉不能很好地处理重叠的物体以及不稳定和不可预测的负载或抓握。机遇：触觉系统可以补充机器视觉系统，使用触觉传感数据来处理重叠的物体和不稳定的握持条件。解决方案：一个配备了独特的仿生触觉传感器的机器人手/手臂，为开发抓取和装配零件的算法提供了一个平台。创新包括开发滑动检测和力锥抓地力调整算法；开发使用触觉反馈的自适应算法来改进握把预成型；物理动力总成部件验证算法；以及具有现实世界不确定性的具有挑战性的算法，这些算法很难用机器视觉来检测。这个项目更广泛的影响/商业潜力将导致机器人拥有更像人类的触觉能力。目前的机器人缺乏触觉感知，依赖于专门的组件馈送器和抓取工具来处理具有预定抓取特征的单个物体。这些项目增加成本，占用空间，消耗时间，特别是当许多不同的对象必须处理。这使得机器人与人类工人相比处于一个明显的劣势，人类工人用手灵巧地处理各种各样的物体。然而，机器人最适合处理对人类来说高度重复或危险的任务。当机器人处理危险材料或制造任务时，它们减轻了人类的负担，同时往往提高了生产率并节省了成本。在第一阶段结束时，我们将开发一个概念验证，以便我们的第二阶段研究可以将系统集成到工业环境中。通过解决在物体姿态、位置和零件间交互中存在错误的物体拾取问题，触觉机器人将改变制造过程中的这一重要部分。这种技术将对制造业和自动化的许多方面产生广泛的影响。

This Small Business Innovation Research (SBIR) Phase I project proposes that haptic robots offer effective andattractive solutions to the common tasks of Bin-Picking and Kitting, which currently require human workers. Apopular application area is programming an industrial robot to work with specific powertrain parts. TheProblem: Bin-picking robots can only manipulate strong parts with simple geometries in structured or semistructuredconfigurations; machine vision deals poorly with overlapping objects and unstable and unpredictableloads or grips. The Opportunity: Haptic systems can compliment machine vision systems using tactile sensorydata to cope with overlapping objects and unstable grip conditions. The Solution: A robotic hand/armequipped with unique biomimetic tactile sensors to make a platform for developing grip algorithms for partspicking and kitting. Innovations include develop algorithms for slip-detection and force-cone grip adjustment;developing adaptive algorithms using tactile feedback to improve grip pre-shaping; validating algorithms withphysical powertrain parts; and challenging algorithms with real-world uncertainties that are difficult to detectusing machine vision.The broader impact/commercial potential of this project will result in robots that have more humanlike hapticcapabilities. Currently robots lack tactile sensing and rely on specialized component feeders and gripping toolsto handle individual objects with predetermined gripping features. These items add cost, occupy space, andconsume time, especially when many different objects must be handled. This puts robots at a significantdisadvantage to human workers who use their hands dexterously to handle an unlimited variety of objects.Nevertheless, robots are best suited to handle tasks that are highly repetitive or dangerous to humans. Whenrobots handle hazardous materials or manufacturing tasks, they relieve humans of these burdens while oftenyielding increased productivity and cost-savings. At the end of Phase I we will have developed a proof ofconcept so that our Phase II research can integrate the system into an industrial environment. By addressing thepicking of objects with errors in object pose, position and part-to-part interaction, haptic robots will transformthis important part of the manufacturing process. Such technology will have widespread impact on manyaspects of manufacturing and automation.