Christopher G. Atkeson 简介

        有一个事实：双足机器人的稳定性问题单靠算法是搞不定的！！！

        在2015 DARPA 机器人挑战赛中，许多参赛团队的机器人使用了Atlas，他们通过安装他们自己的软件并修改来让机器人保持平衡。来自WPI-CMU的阿特拉斯机器人Warner是诸多Atlas中唯一一个没有摔倒或需要重启的机器人。在决赛的两次尝试中，他们都成功走到最后，拿下八分中的七分。这样优异表现的背后，是CMU机器人学院Christopher Atkeson教授组对稳定步态的研究成果，尤其是组里博士生冯思远的工作，冯思远在3D行走方面的论文曾在13年的仿人机器人国际会议Humanoids上获得过大会最佳论文（Best
Paper）的荣誉。

     Christopher G. Atkeson 的经典论文： 《Modeling, stabilit yand control of biped robots—a general framework》

      《连线》记者Nick Stockton也表示了同样的「担忧」，他说，我发誓 Atlas迟早会颠覆现状，而下一件事就是末日审判。加州大学伯克利分校机器人学教授Ken Goldberg也说：「这肯定会引发『恐怖谷』效应，当它被欺负的时候，我们大多数人都会认为它会反击，然后用一束激光消灭了那些欺负它的人。」

       所以，还是那句话：你就不要欺负他好了！

      最终指引到了那个方向：玛格丽特 的 正派社会.

Christopher G. Atkeson 简介:

      转自维基

     CMU机器人学院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

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