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楼梯:斯坦福人工智能机器人项目

STAIR: The STanford Artificial Intelligence Robot Project
课程网址: http://videolectures.net/ijcai09_ng_stair/  
主讲教师: Andrew Ng
开课单位: 斯坦福大学
开课时间: 2009-07-22
课程语种: 英语
中文简介:
本文将介绍楼梯家庭辅助机器人项目,以及导致关键楼梯组件的卫星项目,例如(1)机器人抓取以前未知的物体,(2)从单个静止图像中的深度感知,(3)使用多模态传感器的实际物体识别,以及(4)集成人工智能的软件架构。自1956年诞生以来,人工智能的梦想就是建立一个展示广谱能力和智能的系统。斯泰尔重温这一梦想,并寻求整合到一个单一的机器人平台工具,从所有领域的人工智能,包括学习,视觉,导航,操作,规划,言语和NLP。这与30年来在分散的人工智能子领域工作的趋势形成了鲜明的对比,也代表着一种试图扭转这种趋势的尝试。Stair的目标是成为一个有用的家庭助理机器人,从长远来看,我们设想一个单独的机器人可以执行诸如整理房间、使用洗碗机、取送物品和准备饭菜等任务。在这篇演讲中,Ng将描述我们在让楼梯机器人从办公室周围取走物品以及让楼梯清点办公室物品方面的进展。具体来说,他将描述学习如何抓住以前看不见的物体(包括从洗碗机上卸下物品);概率多分辨率地图,使机器人能够打开或使用门;以及机器人中央凹加外围视觉系统,用于对象识别和跟踪。Ng还将概述一些主要的技术思想,例如从单个静止图像中学习三维重建,以及增强机器人控制的学习算法,这些思想在实现这些楼梯部件方面发挥了关键作用。
课程简介: This talk will describe the STAIR home assistant robot project, and the satellite projects that led to key STAIR components such as (1) robotic grasping of previously unknown objects, (2) depth perception from a single still image, (3) practical object recognition using multimodal sensors, and (4) a software architecture for integrative AI. Since its birth in 1956, the AI dream has been to build systems that exhibit broad-spectrum competence and intelligence. STAIR revisits this dream, and seeks to integrate onto a single robot platform tools drawn from all areas of AI including learning, vision, navigation, manipulation, planning, and speech and NLP. This is in distinct contrast to, and also represents an attempt to reverse, the 30 year old trend of working on fragmented AI sub-fields. STAIR’s goal is a useful home assistant robot, and over the long term, we envision a single robot that can perform tasks such as tidying up a room, using a dishwasher, fetching and delivering items, and preparing meals. In this talk, Ng will describe our progress on having the STAIR robot fetch items from around the office, and on having STAIR take inventory of office items. Specifically, he’ll describe learning to grasp previously unseen objects (including unloading items from a dishwasher); probabilistic multi-resolution maps, which enable the robot to open or use doors; and a robotic foveal plus peripheral vision system for object recognition and tracking. Ng will also outline some of the main technical ideas - such as learning 3-D reconstructions from a single still image, and reinforcement learning algorithms for robotic control - that played key roles in enabling these STAIR components.
关 键 词: 机器人项目; 人工智能; 概率多分辨率; 三维重建
课程来源: 视频讲座网
最后编审: 2020-06-07:王勇彬(课程编辑志愿者)
阅读次数: 185