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

SBIR Phase II: Object Pose Estimation System for Pick and Place Robots
SBIR 第二阶段:拾放机器人的物体姿态估计系统
批准号:
1555822
负责人:
Nicholas Wettels
金额:
$74.62万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-05-01 至 2018-10-31
关键词:

项目摘要

项目成果

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中文摘要
翻译
该项目更广泛的影响/商业潜力是提高制造自动化的成本效益、能源效率和质量,提高工人的生产力并减少重复性运动损伤。这种集成的视觉-触觉系统将比现有的视觉系统便宜3-4倍(购买成本为20,000美元,而现有的视觉系统为65,000 - 80,000美元),提高了当前机器人处理系统的速度和准确性,并促进了重复性,易受伤的手动任务的自动化。通过启用新的机器人应用并提高当前自动化的生产力,该解决方案将有助于美国保持具有竞争力的国内制造业。 2009年,美国有36,190例记录的重复性运动损伤;这些伤害造成的误工时间的中位数为21天(美国劳工统计局)。 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。 直接的商业应用是工业机器人,特别是敏捷制造中的机器人。从长远来看,该技术将应用于个人,医疗保健和军事机器人。目前,工业机器人触觉传感器的市场潜力估计为5.76亿美元至11.5亿美元,预计到2025年将翻一番以上。这个小型企业创新研究(SBIR)第2阶段项目将产生一个组合的视觉-触觉系统,该系统将为机器人提供集成的触觉和视觉,就像人类的手眼协调一样。它采用了一种技术新颖的顺应触觉传感解决方案?橡胶?皮肤?其可以被模制成任何形状因数并且便宜和耐用。 这种先进的蒙皮技术可以解析物体形状、接触/滑动事件以及接触物体的力。 它将独特地融合视觉和触觉信息,用于物体处理和姿态估计,从而产生灵活的机器人系统,更像人类一样处理物体。 这种方法解决了基于视觉的机器人制造中的关键弱点,例如在抓取零件时的遮挡和移位。 目前的工业机器人在处理小型、不规则形状、柔软或易碎部件的能力方面受到限制。现有的解决方案依赖于昂贵而复杂的3D视觉系统或重复的手工劳动。这个解决方案是双重的:(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。
英文摘要
The broader impact/commercial potential of this project is improvement in cost-efficiency, energy-efficiency, and quality in manufacturing automation, increasing worker productivity and reducing repetitive motion injuries. This integrated visual-tactile system will be 3-4 times more inexpensive ($20,000 purchase cost vs. existing $65,000-80,000 vision system), improve the speed and accuracy of current robotic handling systems, and facilitate the automation of repetitive, injury-prone manual tasks. By enabling new robotic applications and increasing productivity in current automation, this solution will help the U.S. maintain a competitive domestic manufacturing sector. In 2009 there were 36,190 logged repetitive motion injuries in the U.S.; the median missed work time from these injuries was 21 days (U.S. Bureau of Labor Statistics). 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. The immediate commercial applications are in industrial robotics, specifically robotics in agile manufacturing. In the long term, the technology will be applied in personal, healthcare, and military robots. The current market potential for tactile sensors for industrial robots is estimated as $576 million - $1.15 billion and expected to more than double by 2025.This Small Business Innovation Research (SBIR) Phase 2 project will result in a combined visual-tactile system that will give robots an integrated sense of touch and vision, much like the hand-eye coordination of humans. It incorporates a technically novel compliant tactile sensing solution?a rubber ?skin? that can be molded into any form factor and is inexpensive and durable. This advanced skin technology can resolve object shape, contact/slip events, and forces of contacted objects. It will uniquely fuse visual and tactile information for object handling and pose estimation resulting in flexible robotic system that handles objects more like humans do. This approach addresses key weaknesses in vision-based robotic manufacturing, such as occlusion and dislodging when parts are grasped. Current industrial robots are restricted in their ability to handle small, irregularly shaped, soft, or fragile parts. Existing solutions rely on expensive and complex 3D-vision systems or repetitive manual labor. This 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.
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SBIR Phase I: Object Pose Estimation System for Pick and Place Robots
  • 批准号:
    1415954
  • 项目类别:
    Standard Grant
  • 资助金额:
    $11.58万
  • 财政年份:
    2014
  • 负责人:
    Nicholas Wettels
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  • 负责人:
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