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

SBIR 第一阶段：拾放机器人的物体姿态估计系统

• 批准号: 1415954
• 负责人: Nicholas Wettels
• 金额: $ 11.58万
• 依托单位: Perception Robotics
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-07-01 至 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1415954&HistoricalAwards=false
• 关键词: SBIR; Phase; Object; Pose; Estimation

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.

该项目更广泛的影响/商业潜力将提高制造业的成本效益和工业自动化，提高工人生产力并减少伤害。机器人的最终用户，即，汽车原始设备制造商和子组件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着的成本优势。在美国劳动力报告的非致命伤害和疾病病例中，43%的伤害是由于身体反应/劳累，62%的疾病病例是由于重复性创伤。这种创新的解决方案将促进重复性、易受伤的手动任务的自动化，并大大提高当前机器人搬运系统的速度、准确性和成本效益。 除了处理，在包装和仓储，危险材料处理，医疗设备和其他精密制造以及炸弹拆除和疏散机器人等军事应用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率，该传感器将帮助美国（和其他发达经济体）保持国内制造业的竞争力。的目标是开发一个视觉触觉传感包的零件处理。 解决办法是双重的：（1）一种新的灵活的触觉传感器，可以定制各种形状的因素;（2）软件融合触觉数据与视觉系统，以估计物体在拾取和放置任务的姿态。 在非结构化环境中，机器人手抓取和操纵物体需要一种耐用、顺应性好、能对各种力和滑动条件做出响应的传感器。其目标是成为第一个商业化的传感包，将触觉和视觉数据与附带的状态估计软件集成在一起。 一家大型软件和游戏公司通过推出一种廉价、易于校准的强大视觉传感器，能够极大地影响机器视觉领域;这对触摸传感也会产生同样的影响吗？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。