??????? 有一個事實：雙足機器人的穩定性問題單靠算法是搞不定的！！！

??????? 在2015 DARPA 機器人挑戰賽中，許多參賽團隊的機器人使用了Atlas，他們通過安裝他們自己的軟件并修改來讓機器人保持平衡。來自WPI-CMU的阿特拉斯機器人Warner是諸多Atlas中唯一一個沒有摔倒或需要重啟的機器人。在決賽的兩次嘗試中，他們都成功走到最后，拿下八分中的七分。這樣優異表現的背后，是CMU機器人學院Christopher Atkeson教授組對穩定步態的研究成果，尤其是組里博士生馮思遠的工作，馮思遠在3D行走方面的論文曾在13年的仿人機器人國際會議Humanoids上獲得過大會最佳論文（Best Paper）的榮譽。

?????Christopher G. Atkeson 的經典論文： 《Modeling, stabilit yand control of biped robots—a general framework》

????? 《連線》記者Nick Stockton也表示了同樣的「擔憂」，他說，我發誓 Atlas遲早會顛覆現狀，而下一件事就是末日審判。加州大學伯克利分校機器人學教授Ken Goldberg也說：「這肯定會引發『恐怖谷』效應，當它被欺負的時候，我們大多數人都會認為它會反擊，然后用一束激光消滅了那些欺負它的人。」

?????? 所以，還是那句話：你就不要欺負他好了！

????? 最終指引到了那個方向：瑪格麗特 的 正派社會.

Christopher G. Atkeson 簡介:

????? 轉自維基

???? CMU機器人學院Christopher Atkeson教授

Early life and education

Atkeson graduated summa cum laude from Harvard University in 1981 with an A.B. in Biochemistry. He received his S.M. degree inApplied Mathematics in the same year, also from Harvard. He then attended theMassachusetts Institute of Technology and received his PhD in Brain and Cognitive Science from the in 1986, advised by Emilio Bizzi.

Career

Before joining the faculty at CMU in 2000, he was an Assistant, then Associate Professor in the department of Brain and Cognitive Sciences at MIT from 1986-1993, an Associate Professor at the College of Computing,Georgia Institute of Technology from 1994 to 2000.

Honors and awards

• National Science Foundation Engineering Initiation Award, 1987-1988.
• National Science Foundation Presidential Young Investigator Award, 1988-1993.
• W. M. Keck Foundation Assistant Professorship in Biomedical Engineering, 1988-1990.
• Alfred P. Sloan Research Fellow, 1989-1991.
• W. M. Keck Foundation Associate Professorship in Biomedical Engineering, 1990-1991.
• Teaching Award from the MIT Graduate Student Council, 1990.
• Edenfield Faculty Fellowship Award, 1995.
• Elected by faculty to College of Computing Dean’s Advisory Committee, 1995–1996, 1996–1997.
• Finalist, Best Paper Award, ICRA 2000.

References

Atkeson, C.G.; Moore, A.W.; Schaal, S. (1997). "Locally weighted learning".Artificial Intelligence Review 11 (1): 11–73.

External links

• Home Page

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