Kris K Hauser
Primary Research Area
- Artificial Intelligence
Kris Hauser is an Associate Professor at the Pratt School of Engineering at Duke University with a joint appointment in the Electrical and Computer Engineering Department and the Mechanical Engineering and Materials Science Department. He received his PhD in Computer Science from Stanford University in 2008, bachelor's degrees in Computer Science and Mathematics from UC Berkeley in 2003, and worked as a postdoctoral fellow at UC Berkeley. He then joined the faculty at Indiana University from 2009-2014, where he started the Intelligent Motion Lab. He is a recipient of a Stanford Graduate Fellowship, Siebel Scholar Fellowship, and the NSF CAREER award.
For more information
- Robot motion planning and control, semiautonomous robots, and integrating perception and planning, as well as applications to intelligent vehicles, robotic manipulation, robot-assisted medicine, and legged locomotion.
Selected Articles in Journals
- K. Hauser. Learning the Problem-Optimum Map: Analysis and Application to Global Optimization in Robotics. In IEEE Transactions on Robotics, PP(99)1-12, 2016
- K. Hauser and Y. Zhou. Asymptotically Optimal Planning by Feasible Kinodynamic Planning in State-Cost Space. IEEE Transactions of Robotics, 32(6): 1431-1443, 2016.
Articles in Conference Proceedings
- K. Hauser. Continuous Pseudoinversion of a Multivariate Function: Application to Global Redundancy Resolution. Workshop on the Algorithmic Foundations of Robotics (WAFR), 2016.
- A. Rocchi, B. Ames, J. Li, and K. Hauser. Stable Simulation of Underactuated Compliant Hands. IEEE Int'l. Conf. on Robotics and Automation (ICRA), 2016.
- O. Ramos and K. Hauser. Generalizations of the Capture Point to Nonlinear Center of Mass Paths and Uneven Terrain. IEEE-RAS Int'l Conference on Humanoid Robots, November, 2015.