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The perception problem and the impact on robotics and computer vision

机译:感知问题及其对机器人技术和计算机视觉的影响

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Why is there a perception problem in robotics? Given the increases in the speed of computer hardware and technology which has followed Moore's Law, why haven't there been commensurate advances in computer perception technology, which would enable a robot to respond appropriately to its environment? Perhaps the algorithms used for perception are not appropriate for the problem? The computer vision problem was assumed to be easy, and the supposedly more difficult challenges of problem solving and decision making were tackled first. As it turned out, problem solving and decision making were handled relatively easily by symbolic representations and predicate logic, however, the perception of the real world turned out to be much more difficult. What are the algorithms that have been used for perception in robotics and why do they sometimes fail at reproducing human-like behavior? How can we learn from biological systems which, through evolution, have made great advances in solving the difficult problems of perception and classification
机译:为什么机器人技术中存在感知问题?鉴于遵循摩尔定律的计算机硬件和技术的速度在不断提高,为什么计算机感知技术没有得到相应的发展,这将使机器人能够对环境做出适当的响应?也许用于感知的算法不适用于该问题?假定计算机视觉问题很容易,并且首先解决了解决问题和决策的难题。事实证明,通过符号表示和谓词逻辑可以相对轻松地解决问题和决策,但是,对现实世界的感知却要困难得多。机器人技术中用于感知的算法是什么?为什么它们有时无法重现类似人的行为?我们如何从生物系统中学习,通过进化,生物系统在解决感知和分类的难题方面取得了长足的进步

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