SBIR Phase I: Object Pose Estimation System for Pick and Place Robots

该项目的广泛影响/商业潜力将提高制造业的成本效率和工业自动化，提高工人生产率并减少伤害。机器人的最终用户，即汽车原始设备制造商和子装配供应商，将能够通过使用更便宜的系统自动化新的装配任务来实现显著的成本优势。在美国劳动力报告的非致命性伤害和疾病病例中，43%的伤害是由于身体反应/劳累造成的，62%的疾病病例是由于重复性创伤造成的。这种创新的解决方案将促进重复性，容易受伤的手动任务的自动化，并大大提高当前机器人处理系统的速度，准确性和成本效益。除了搬运之外，在包装和仓储、危险材料搬运、医疗设备和其他精密制造以及军事应用（如炸弹拆除和疏散机器人）方面也有巨大的市场潜力。通过实现新的机器人应用和提高当前自动化的生产力，这种传感器将帮助美国（和其他发达经济体）保持有竞争力的国内制造业。小企业创新研究（SBIR）第一阶段项目？S的目标是开发一种用于零件处理的视觉触觉传感包。解决方案有两个方面：(1)一种新的柔性触觉传感器，可以根据各种形状因素进行定制；(2)将触觉数据与视觉系统融合的软件，用于估计拾取任务中物体的姿态。在非结构化环境中，机器人手对物体的抓取和操纵需要一个耐用、柔顺、对各种力和滑移条件做出响应的传感器。目标是成为第一个商业可用的传感封装，集成触觉和视觉数据以及伴随的状态估计软件。一家大型软件和游戏公司通过引入廉价且易于校准的强大视觉传感器，极大地影响了机器视觉领域；这将做同样的触摸感应？我们的团队多年来一直在研究这种触觉传感器的理想特性，并发现了一种以廉价、坚固的形式生产它们的方法。

The broader impact/commercial potential of this project will enable improved cost-efficiency and industrial automation in manufacturing, increasing worker productivity and reducing injuries. The end-users of the robots, i.e., automotive original-equipment-manufacturers and subassembly suppliers, will be able to achieve significant cost advantages by automating new assembly tasks with more inexpensive systems. Of the non-fatal injuries and illness cases reported in the U.S. workforce, 43% of injuries were due to bodily reaction/exertion, and 62% of illness cases were due to repetitive trauma. This innovative solution will facilitate the automation of repetitive, injury-prone manual tasks and greatly improve the speed, accuracy, and cost-efficiency of current robotic handling systems. Beyond handling, there is significant market potential in packaging and warehousing, hazardous materials handling, medical device and other precision manufacturing, and military applications such as bomb defusal and evacuation robots. By enabling new robotic applications and increasing productivity in current automation, this sensor will help the U.S. (and other developed economies) maintain a competitive domestic manufacturing sector.This Small Business Innovation Research (SBIR) Phase I project?s goal is to develop a visual-tactile sensing package for parts handling. The solution is two-fold: (1) A new flexible tactile sensor that can be tailored to a wide variety of form factors; (2) Software to fuse the tactile data with a vision system to estimate pose of objects in pick-and-place tasks. Object grasping and manipulation by robotic hands in unstructured environments demands a sensor that is durable, compliant, and responsive to various force and slip conditions. The goal is to be the first commercially available sensing package that integrates tactile and visual data with accompanying software for state estimation. A large software and gaming company was able to greatly impact the machine vision space by introducing an inexpensive, easily calibrated robust visual sensor; this will do the same for touch sensing ? our team has studied the desirable properties of such tactile sensors for years and discovered a way to produce them in an inexpensive, robust format.