Abstract
This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.
| Original language | English |
|---|---|
| Article number | 030801 |
| Journal | Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME |
| Volume | 137 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2015 Mar 1 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Information Systems
- Instrumentation
- Mechanical Engineering
- Computer Science Applications
Cite this
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Tips on stochastic optimal feedback control and Bayesian spatiotemporal models : Applications to robotics. / Choi, Jongeun; Milutinović, Dejan.
In: Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME, Vol. 137, No. 3, 030801, 01.03.2015.Research output: Contribution to journal › Article
TY - JOUR
T1 - Tips on stochastic optimal feedback control and Bayesian spatiotemporal models
T2 - Applications to robotics
AU - Choi, Jongeun
AU - Milutinović, Dejan
PY - 2015/3/1
Y1 - 2015/3/1
N2 - This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.
AB - This tutorial paper presents the expositions of stochastic optimal feedback control theory and Bayesian spatiotemporal models in the context of robotics applications. The presented material is self-contained so that readers can grasp the most important concepts and acquire knowledge needed to jump-start their research. To facilitate this, we provide a series of educational examples from robotics and mobile sensor networks.
UR - http://www.scopus.com/inward/record.url?scp=84940655707&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84940655707&partnerID=8YFLogxK
U2 - 10.1115/1.4028642
DO - 10.1115/1.4028642
M3 - Article
VL - 137
JO - Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME
JF - Journal of Dynamic Systems, Measurement and Control, Transactions of the ASME
SN - 0022-0434
IS - 3
M1 - 030801
ER -