Robovie2係由日本京都市「國際電氣通信基礎技術研究所」(ATR)的智慧機器人部門研製。銀髮族先在家裡以行動裝置輸入所需商品清單,傳送到超市內的機器人系統主機,主機再將清單無線傳輸給Robovie2。
到達超市時,Robovie2會叫出長者姓名並上前迎接,陪伴對方一起進入購物區。長者可將購物籃掛在Robovie2的手上,它會依購物清單引導長者到物品所在處,也會跟長者聊要買的東西,譬如「蜜柑好好吃喔,我也想吃一個」。
This blog is daily record about paper or research ME712-2 and EM330 done.
Firefighters enlisted the help of a robot to dramatically reduce the time spent dealing with a fire at a Wokingham industrial estate.
Royal Berkshire Fire and Rescue Service used the Remotely Operated Vehicle (ROV) to handle the acetylene cylinder at Toutley Depot in Old Forest Road, which had caught fire while a worker used it for welding.
Standard operational procedure would have meant a 200-metre cordon being set up for 24 hours, which would have meant closing Toutley Depot, the A329 and evacuating some residents.
The fire crew was called to the incident at 12.45pm on Thursday, September 24.
By sending the ROV into the workshop the crews could receive vital information about the incident without putting themselves in danger.
The ROV has in-built specialist tools, including a thermal imaging camera and filming equipment, which allows firefighters to assess the situation from a safe distance.
The ROV found the cylinder was cool and operators then turned off the valve using a spanner attached to the robot.
Station manager Jess James, from Caversham Road station, said: “Using the ROV meant that we could deal with the incident in around three-and-a-half hours, rather than the 24 hours it would traditionally take.
“This not only means that the premises could be handed back to the owners in a shorter space of time, but also that fire crews are freed up more quickly and are available to attend other incidents.”
http://www.getwokingham.co.uk/news/s/2058394_robot_comes_to_aid_of_fire_crew_at_depot_blaze
2009 APR 20 - (VerticalNews.com) -- According to a study from Taiwan, "This paper proposes a novel real-time machine video-based flame and smoke detection method that can be incorporated with a surveillance system for early alerts. Automatic monitoring systems use the motion history detection algorithm to register the possible flame and smoke position in a video and then analyze the spectral, spatial and temporal characteristics of the flame and smoke regions in the image sequences."
"The spectral probability density is represented by comparing the flame and smoke color histogram model, where HSI color spaces are used. The spatial probability density is represented by computing the flame and smoke turbulent phenomena with the relation of perimeter and area. Statistical distribution of the spectral and spatial probability density is weighted with the fuzzy reasoning system to give the potential flame and smoke candidate region. The temporal probability density is represented by extracting the flickering area with level crossing and separating the alias objects from the flame and smoke region. Then, the continuously adaptive mean shift (CAMSHIFT) vision tracking algorithm is employed to provide feedback of the flame and smoke real-time position at a high frame rate," wrote C.C. Ho and colleagues.
The researchers concluded: "Experimental results under a variety of conditions show that the proposed method is capable of detecting flame and smoke reliably."
Ho and colleagues published their study in Measurement Science & Technology (Machine vision-based real-time early flame and smoke detection. Measurement Science & Technology, 2009;20(4):45502).
For more information, contact C.C. Ho, National Yunlin University Science & Technology, Dept. of Mech Engineering, Yunlin 64002, Taiwan.
Publisher contact information for the journal Measurement Science & Technology is: IOP Publishing Ltd., Dirac House, Temple Back, Bristol BS1 6BE, England.
Keywords: Emerging Technologies, Fuzzy Logic, Machine Learning, Machine Vision, Measurement Science.
This article was prepared by VerticalNews Robotics & Machine Learning editors from staff and other reports. Copyright 2009, VerticalNews Robotics & Machine Learning via VerticalNews.com.For the moment, ports above COM10 are not named COM10. They are named \\.\COM10 and so on. Except that some drivers use names like USB port 1 for all ports. Don't forget to double \ chars when inside quotes. E.g. "\\\\.\\COM10"
Manually edit the virtual machine's configuration file (.vmx on Windows hosts, .cfg on Linux hosts). Change the following line from:
serial0.fileName = "COM10"
to
serial0.fileName = "\\.\COM10"
Power on the virtual machine to verify the COM10 serial port is operational.
Assume you have two projects - Project1 and project2 and you want to copy one dialog from Project1 to Project2. Just follow the steps -
For Visual Studio 6.0
1) Load project2 workspace in visual studio.
2) Now Browse and load Project1’s rc file. While opening resource file, select “Open As” as “Resources”.
3) Now drag your required dialog from project1’s resource tree and drop it to your resource tree.
4) You’ve successfully copied dialog from one project to another!
For Visual Studio 2005 and siblings
1) Open your IDE without any solutions loaded.
2) open both RC files into the IDE.
3) Now take Project2 RC file, right click on the dialog you want to export and copy it.
4) Now take Project1 RC file, right click and paste.
5) You see, now the dialog is imported from project1 to Project2.
Well, special thanks to Mike and Alan for their contribution for the trick in Visual Studio 2005.
在這個日本最精密機器人的柔軟矽膠皮膚下,處理器記錄並評估各種訊息。這個高130公分、重33公斤的小型機器人CB2可以像人類嬰兒一般的學習。
這個長得彷彿真人的兒童機器人代號CB2。研究人員說,它會根據與人類之間的互動,注視人類表情變化及模仿小嬰兒與母親之間的關係,慢慢發展社交技巧。
大阪大學教授淺田稔表示:「嬰兒會的事情很少,但很會學習。」
研究團隊正試著讓機器人像個小嬰孩一般,評估母親的各種表情,將這些表情整合成幾個基本類別,例如高興和悲傷。這個研究,集合機器人工程師、人腦研究專家、心理學家與其他領域的專業人士,由日本的行政法人「科學技術振興機構」贊助。
淺田表示,在CB2的淺灰色橡皮皮膚之下,有197條壓力感應器,可以辨識人類的觸感,它的眼睛也裝有攝影機,會錄下表情變化,記住後就尋找搭配的身體感受,送到電路板上。
淺田2007年推出CB2,此後技術不斷進步。他表示,這2年來,CB2已經藉著人類協助,自行學會走路,現在可藉由氣壓驅動的51條「肌肉」,平穩的在室內移動自如。
淺田希望未來的科技可以創造一種「機器人類」,擁有介於人類與黑猩猩等靈長類之間的學習能力。他也希望CB22年內會講基本字句,達到2歲小孩的智慧水準。
【聯合報╱國際中心/法新社日本吹田5日電】
游姿流暢自然
日 本「每日新聞」二十一日報導,現年四十八歲的山本自一九八○年代後期投入機器魚的研發,後於一九九五年推出第一代機器鯛魚,去年七月終於完成游水姿態流暢 自然的第三代機器鯛魚。第三代機器鯛魚長八十公分、重七公斤,魚鱗等外觀以矽膠材質製成,尾鰭加裝的機器關節,可進一步提升機器鯛魚的瞬間爆發力,整體動 作也更流暢自然。
由於機器鯛魚的動作非常逼真,「和機器鯛魚放在一起游水的魚兒都沒發現異狀,表現跟自然狀態時一樣」。山本表示:「機器魚的噪音低,可在不驚擾魚群的情況下進行海洋調查。」
一般潛水調查機器利用螺旋槳推進時,可能勾纏到海藻等異物,若使用搭載攝影機的機器鯛魚,就能避免這樣的危險,廣泛調查各種海洋資訊。
NASA有興趣合作
山 本現正運用機器鯛魚的研發成果,進一步投入機器魟的研究,據說機器魟的外型能夠大幅降低水阻力,可能達到如同鯊魚或海豚般的高速游水速度。山本也說:「流 暢的尾鰭動作技術,還能運用於醫學外科精密儀器或太空作業用機器人等研發工作。」美國國家航太總署(NASA)也注意到山本的研究,日後雙方或許有機會合 作。
〔自由時報編譯鄭曉蘭/綜合報導〕
Essex University 所研發出的電子魚