Planning/control 2012-12-21

Motion planning with uncertainty

Andrea Censi, Adam Nilsson, and Richard M. Murray. Motion planning in observations space with learned diffeomorphism models. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), 2860–2867. Karlsruhe, Germany, 5 2013. pdfdoi supp. materialbibtex

Using learned diffeomorphism models of the dynamics of cameras and range-finders, we formulate motion planning as a planning problem in the observations space. Nodes/states are (uncertain) images; actions/edges are (uncertain) diffeomorphisms.

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Andrea Censi, Daniele Calisi, Alessandro De Luca, and Giuseppe Oriolo. A Bayesian framework for optimal motion planning with uncertainty. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA). Pasadena, CA, May 2008. pdfdoi supp. material slidesbibtex

How to get to your goal without getting lost. This was my Master's degree final thesis.

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Bioplausible visual control

Shuo Han, Andrea Censi, Andrew D. Straw, and Richard M. Murray. A bio-plausible design for visual pose stabilization. In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 5679–5686. Taipei, Taiwan, October 2010. pdfdoi video slidesbibtex

Stabilizing hovering for an helicopter using a bio-plausible strategy.

Andrea Censi, Shuo Han, Sawyer B. Fuller, and Richard M. Murray. A bio-plausible design for visual attitude stabilization. In Proceedings of the 48th IEEE Conference on Decision and Control. Shanghai, China, December 2009. pdfdoi slidesbibtex

This paper describes a "bio-plausible" control strategy for stabilizing the attitude in SO(3) of a flying body. The follow-up paper considers the SE(3) case.