PFI-TT: Robotic Dexterity for Material Handling

PFI-TT：用于物料搬运的机器人灵巧性

• 批准号: 2329795
• 负责人: Matei Ciocarlie
• 金额: $ 54.82万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2329795&HistoricalAwards=false
• 关键词: PFI; TT; Robotic; Dexterity; Material

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project consists of steps towards a more effective and robust supply chain for our economy. Recent years have highlighted the critical importance of the material handling industry to our national economy: a snarled supply chain reverberates everywhere in society. The number one challenge in this industry is that the difficult ergonomics and repetitive nature make many tasks injury-prone and unsuitable for workers. Nevertheless, automation has alleviated this problem only to a small degree: robotics has achieved only small market penetration in material handling, and one of the key reasons is the absence of critical technology pertaining to versatile and dexterous robotic material handling. Currently, flexible robotic manipulators able to handle dexterous tasks are largely lacking from the field. Developing such manipulators would both enhance our scientific understanding of motor control tasks and motor learning and have an immediate impact in increasing supply chain efficiency.The proposed project aims to develop and translate such technology to the marketplace. We build on recent work from the principal investigator’s team, which demonstrated complex robotic manipulation tasks, such as large in-hand object reorientation with finger gaiting, while simultaneously securing the manipulated object. This result was achieved by combining novel exploration methods for deep reinforcement learning of motor skills with the optics-based tactile fingers previously developed by the PFI team. The project aims to further develop learning-based methods for extrinsic manipulation, where the robot uses external surfaces to impart the desired movement, a strategy that will help reduce the kinematic requirements on the hand itself. This will in turn enable hands to be mounted on commercial robot arms, resulting in a complete automation station. While the previous work informing the PFI project relied exclusively on tactile and proprioceptive sensing to demonstrate dexterity, deployment for complete tasks requires the addition of vision sensors, and thus methods for learning multimodal, visuotactile control policies for dexterous extrinsic manipulation. The PFI team will apply this research to the concrete task of automating the sortation system induction process with dexterous package re-orientation, a commonly found task in the distribution centers that are the backbone of our supply chain.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这种伙伴关系对创新 - 技术翻译（PFI -TT）项目的更广泛的影响/商业潜力包括迈向对我们经济的更有效，更强大的供应链的步骤。近年来，材料处理行业对我们的国民经济的重要性至关重要：社会中各地的任何供应链都回荡了。在这个行业中，第一个挑战是，艰难的人体工程学和重复性的性质使许多任务容易受伤，并且不适合工人。然而，自动化仅在很小的程度上缓解了这个问题：机器人技术在材料处理中仅实现了少量的市场渗透，关键原因之一是缺乏与多功能和灵活的机器人材料处理有关的关键技术。当前，该领域的灵活机器人操纵器可以处理灵巧的任务。开发此类操纵器既可以增强我们对运动控制任务和运动学习的科学理解，并且会对提高供应链效率产生直接影响。该项目旨在开发和将这种技术转化为市场。我们基于主要调查员团队的最新工作，该团队展示了复杂的机器人操纵任务，例如手指步态的大型内在对象重新定位，同时又确保了受操纵的对象。通过将新颖的探索方法与以前由PFI团队开发的基于光学的触觉手指结合起来，以深入强化运动技能的深度增强方法来实现这一结果。该项目旨在进一步开发基于学习的外部操作方法，在该方法中，机器人使用外部表面来赋予所需的运动，该策略将有助于减少手中的运动要求。反过来，这将使手安装在商业机器人臂上，从而导致一个完整的自动化站。在先前告知PFI项目的工作仅依赖于触觉和本体感受传感器来证明灵巧性，但要进行完整任务的部署需要添加视觉传感器，从而为学习多模式，视觉控制政策的方法用于灵敏性脱纤维限制。 PFI团队将将这项研究应用于具有灵活的包装重新定位的具体任务，即在分销中心中通常发现的任务是我们供应链的骨干。该奖项反映了NSF的法定任务，并认为通过基金会的知识优点和广泛的crietia crietia criperia crigitia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia criperia cribitia criperia scriperia scriptiation。