Standard
Harvard
Mihaylova, L, Lefebvre, T, Bryunincks, H, Gadeyne, K & De Schutter, J 2003,
A comparison of decision making criteria and optimization methods for active robotic sensing. in I Dimov, I Lirkov, S Margenov & Z Zlatev (eds),
Numerical Methods and Applications: 5th International Conference, NMA 2002 Borovets, Bulgaria, August 20–24, 2002 Revised Papers. Lecture Notes in Computer Science, vol. 2542, Springer, Berlin, pp. 316-324.
https://doi.org/10.1007/3-540-36487-0_35
APA
Mihaylova, L., Lefebvre, T., Bryunincks, H., Gadeyne, K., & De Schutter, J. (2003).
A comparison of decision making criteria and optimization methods for active robotic sensing. In I. Dimov, I. Lirkov, S. Margenov, & Z. Zlatev (Eds.),
Numerical Methods and Applications: 5th International Conference, NMA 2002 Borovets, Bulgaria, August 20–24, 2002 Revised Papers (pp. 316-324). (Lecture Notes in Computer Science; Vol. 2542). Springer.
https://doi.org/10.1007/3-540-36487-0_35
Vancouver
Mihaylova L, Lefebvre T, Bryunincks H, Gadeyne K, De Schutter J.
A comparison of decision making criteria and optimization methods for active robotic sensing. In Dimov I, Lirkov I, Margenov S, Zlatev Z, editors, Numerical Methods and Applications: 5th International Conference, NMA 2002 Borovets, Bulgaria, August 20–24, 2002 Revised Papers. Berlin: Springer. 2003. p. 316-324. (Lecture Notes in Computer Science). doi: 10.1007/3-540-36487-0_35
Author
Bibtex
@inbook{c0b54ef4e7cb45748a74b4233d10e6d2,
title = "A comparison of decision making criteria and optimization methods for active robotic sensing",
abstract = "This work presents a comparison of decision making criteria and optimization methods for active sensing in robotics. Active sensing incorporates the following aspects: (i ) where to position sensors, and (ii ) how to make decisions for next actions, in order to maximize information gain and minimize costs. We concentrate on the second aspect: “Where should the robot move at the next time step?”. Pros and cons of the most often used statistical decision making strategies are discussed. Simulation results from a new multisine approach for active sensing of a nonholonomic mobile robot are given.",
keywords = "active sensing, decsion making, intelligent systems, autonomous robotic systems",
author = "Lyudmila Mihaylova and Tine Lefebvre and Herman Bryunincks and Klaas Gadeyne and {De Schutter}, Joris",
note = "The original publication is available at www.springerlink.com",
year = "2003",
doi = "10.1007/3-540-36487-0_35",
language = "English",
isbn = "9783540006084",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "316--324",
editor = "Ivan Dimov and Ivan Lirkov and Svetozar Margenov and Zahari Zlatev",
booktitle = "Numerical Methods and Applications",
}
RIS
TY - CHAP
T1 - A comparison of decision making criteria and optimization methods for active robotic sensing
AU - Mihaylova, Lyudmila
AU - Lefebvre, Tine
AU - Bryunincks, Herman
AU - Gadeyne, Klaas
AU - De Schutter, Joris
N1 - The original publication is available at www.springerlink.com
PY - 2003
Y1 - 2003
N2 - This work presents a comparison of decision making criteria and optimization methods for active sensing in robotics. Active sensing incorporates the following aspects: (i ) where to position sensors, and (ii ) how to make decisions for next actions, in order to maximize information gain and minimize costs. We concentrate on the second aspect: “Where should the robot move at the next time step?”. Pros and cons of the most often used statistical decision making strategies are discussed. Simulation results from a new multisine approach for active sensing of a nonholonomic mobile robot are given.
AB - This work presents a comparison of decision making criteria and optimization methods for active sensing in robotics. Active sensing incorporates the following aspects: (i ) where to position sensors, and (ii ) how to make decisions for next actions, in order to maximize information gain and minimize costs. We concentrate on the second aspect: “Where should the robot move at the next time step?”. Pros and cons of the most often used statistical decision making strategies are discussed. Simulation results from a new multisine approach for active sensing of a nonholonomic mobile robot are given.
KW - active sensing
KW - decsion making
KW - intelligent systems
KW - autonomous robotic systems
U2 - 10.1007/3-540-36487-0_35
DO - 10.1007/3-540-36487-0_35
M3 - Chapter
SN - 9783540006084
T3 - Lecture Notes in Computer Science
SP - 316
EP - 324
BT - Numerical Methods and Applications
A2 - Dimov, Ivan
A2 - Lirkov, Ivan
A2 - Margenov, Svetozar
A2 - Zlatev, Zahari
PB - Springer
CY - Berlin
ER -
