Computer graphics (2nd ed. in C): principles and practice
Computer graphics (2nd ed. in C): principles and practice
Decision-Theoretic Cooperative Sensor Planning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constraint-Based Sensor Planning for Scene Modeling
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Comparison of Decision Making Criteria and Optimization Methods for Active Robotic Sensing
NMA '02 Revised Papers from the 5th International Conference on Numerical Methods and Applications
CVPR '98 Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
A Multiple Attribute Utility Theory Approach to Ranking and Selection
Management Science
| Hi-index | 0.00 |
Positioning multiple sensors for acquisition of a a given environment is one of the fundamental research areas in various fields, such as military scouting, computer vision and robotics. In this paper, we propose a framework for locating an configuring a set of given sensors in a synthetically generated terrain with multiple objectives of maximization of visibility of the terrain, maximization of stealth of the sensors and minimization of cost of the sensors. Because of their utility-independent nature, these complementary and conflicting objectives are represented by a multiplicative global utility function based on multi-attribute utility theory. In addition to theoretic foundations, we also present how a Genetic Algorithms can be applied to maximize the global utility function for a given terrain.