使用动态红外和目标检测的夜视机器人

Devesh Abhyankar, Gurumoorty Suresh, Hrithik Sambhaji Karjule, Parth Bhardwaj, Harish Muleva, Anurag Mahajan
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引用次数: 0

摘要

机器人技术作为工程领域的延伸,对人类的进化起到了很大的支持作用。通过机器人技术,即使是复杂的任务也可以通过简单的自动化和减少人为干预来简化。机器人甚至减少了人类的工作量,提高了完成任何任务的效率和准确性。机器人技术已经扩展并帮助了许多领域的发展和演变,如农业、国防、育儿、医疗保健、工业、航空航天等。用于调查或勘探的机器人可用于野生动物,工业和国防领域的许多用途。这些机器人能够进入人类容易受到攻击的区域,并且可以在合理的距离内进行控制。该机器人由于其体积小,内置夜视摄像头,使其成为监视和探索的非常有用的工具。这个机器人有能力从远处控制,它将使用户在夜间(或黑暗中)清楚地看到物体。这些类型的机器人已经存在了几年,只是为了增加新的发展。最近的发展涉及到物联网(IoT)的集成,以远程控制机器人并从中获取信息。然而,最新增加的是一个新概念,被称为动态红外,它涉及到控制红外光的强度,以产生更好的图像。此外,加上使用机器学习算法的对象检测,它可以预测它可能面临的障碍类型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Night Vision Bot using Dynamic IR and Object Detection
Robotics as an extension to the field of Engineering has been of great support to the evolution of mankind. Through robotics, even complex tasks can be simplified through simple automation and decreased human intervention. Robots even reduce the workload on humans and increase the level of efficiency and accuracy in doing any task. Robotics has branched out and helped in the development and evolution of many fields such as agriculture, defense, parenting, healthcare, industry, aerospace and, so on. The robots which are used for survey or exploration can be used for many purposes in the fields of Wildlife, Industry and, Defense. These robots are capable of going to the areas which are vulnerable for humans, and they can be controlled from a reasonable distance. This robot due to its small size and in-built night vision camera makes it a very useful tool for surveillance and exploration. This robot has the ability to be controlled from a distance and it will enable the users to view objects clearly at night (or in darkness). These types of robots have been in existence for a couple of years, only for new developments to be added to them. The very recent development involves the integration of IoT (Internet of Things) to control the robot remotely and obtain information from it. The latest addition however is the addition of a new concept, known as Dynamic IR, which involves the control of the intensity of the IR light to produce better images. Moreover, with the addition of Object Detection using Machine Learning Algorithms, it can predict what type of obstacle it may face.
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