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TROB
2010
129views more  TROB 2010»
13 years 5 months ago
A Probabilistic Particle-Control Approximation of Chance-Constrained Stochastic Predictive Control
—Robotic systems need to be able to plan control actions that are robust to the inherent uncertainty in the real world. This uncertainty arises due to uncertain state estimation,...
Lars Blackmore, Masahiro Ono, Askar Bektassov, Bri...
NIPS
1998
13 years 8 months ago
Learning Nonlinear Dynamical Systems Using an EM Algorithm
The Expectation Maximization EM algorithm is an iterative procedure for maximum likelihood parameter estimation from data sets with missing or hidden variables 2 . It has been app...
Zoubin Ghahramani, Sam T. Roweis
ICRA
2007
IEEE
148views Robotics» more  ICRA 2007»
14 years 1 months ago
Dynamic Obstacle Avoidance in uncertain environment combining PVOs and Occupancy Grid
— Most of present work for autonomous navigation in dynamic environment doesn’t take into account the dynamics of the obstacles or the limits of the perception system. To face ...
Chiara Fulgenzi, Anne Spalanzani, Christian Laugie...
EOR
2011
127views more  EOR 2011»
13 years 2 months ago
Methodology for determining the acceptability of system designs in uncertain environments
In practice, managers often wish to ascertain that a particular engineering design of a production system meets their requirements. The future environment of this design is likely...
Jack P. C. Kleijnen, Henri Pierreval, Jin Zhang
ASPDAC
2008
ACM
119views Hardware» more  ASPDAC 2008»
13 years 9 months ago
A stochastic local hot spot alerting technique
- With the increasing levels of variability in the behavior of manufactured nano-scale devices and dramatic changes in the power density on a chip, timely identification of hot spo...
Hwisung Jung, Massoud Pedram