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» Sampling-Based Motion Planning Using Predictive Models
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TROB
2010
129views more  TROB 2010»
14 years 8 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...
ICML
2007
IEEE
15 years 10 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
VR
2003
IEEE
267views Virtual Reality» more  VR 2003»
15 years 3 months ago
An Experiment Comparing Double Exponential Smoothing and Kalman Filter-Based Predictive Tracking Algorithms
We present an experiment comparing double exponential smoothing and Kalman filter-based predictive tracking algorithms with derivative free measurement models. Our results show t...
Joseph J. LaViola Jr.
UIST
2003
ACM
15 years 2 months ago
Rhythm modeling, visualizations and applications
People use their awareness of others' temporal patterns to plan work activities and communication. This paper presents algorithms for programatically detecting and modeling t...
James Begole, John C. Tang, Rosco Hill
VLDB
2012
ACM
360views Database» more  VLDB 2012»
13 years 5 months ago
An adaptive updating protocol for reducing moving object database workload
In the last decade, spatio-temporal database research focuses on the design of effective and efficient indexing structures in support of location-based queries such as predictive...
Su Chen, Beng Chin Ooi, Zhenjie Zhang