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Cloud-Based Services for Cooperative Robot Learning of 3D Object Detection and Recognition

机译:基于云的合作机器人学习3D对象检测和识别的服务

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Some of the problems preventing the widespread adoption of advanced service robots are (1) cost, (2) power consumption, (3) perceptual capabilities, (4) knowledge management, (5) reasoning capabilities, and (6) compute power. Improvement along these dimensions will make adoption of service robots with advanced capabilities much more widespread. We propose the use of real time cloud computation as one means to enable these improvements. This paper presents a case study on the use of a cloud computing platform to support robotics applications, allowing robots to offload heavy compute tasks such as machine vision to cloud infrastructure. We specifically aim to give a widely distributed group of robots the ability to learn 3D objects cooperatively for detection and recognition. Participating robots can share their knowledge with others via our cloud-based services. Experiments with a proof of concept prototype demonstrate the feasibility of the use of cloud platforms to deliver improved perceptual, knowledge management, and reasoning capabilities while keeping the cost and power consumption of the robot low.
机译:防止广泛使用先进服务机器人的一些问题是(1)成本,(2)功耗,(3)感知能力,(4)知识管理,(5)推理能力,(6)计算权力。沿着这些尺寸的改进将采用具有高级功能的服务机器人更广泛。我们建议使用实时云计算作为一种方法来实现这些改进。本文介绍了使用云计算平台支持机器人应用的案例研究,允许机器人卸载重型计算任务,如机器视觉到云基础架构。我们专门旨在为一个广泛分布的机器人组成一个能够学习3D对象的合作检测和识别。参与机器人可以通过我们基于云的服务与他人分享他们的知识。概念原型证明的实验证明了使用云平台的可行性,以提供改进的感知,知识管理和推理能力,同时保持机器人的成本和功耗低。

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