Home /Research /Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots
OTHER

Learning Probabilistic Models for Decision-Theoretic Navigation of Mobile Robots

Daniel Nikovski, Illah Nourbakhsh

Year
2000
Citations
18

Abstract

A detailed analysis of the ECL interaction between luminol and tris(2,2'-bipyridyl)dichlororuthenium(ii) (Ru(bpy)<sub>3</sub><sup>2+</sup>) is required before using them in ECL systems for multianalyte detection purposes. Spectro-electrochemiluminescence demonstrates that not only must the emission properties be considered, but also their additional optical characteristics are involved in the explanation of the interaction mechanism between these luminophores.

Keywords

Mobile robotProbabilistic logicComputer scienceRobotArtificial intelligenceDecision theoryMachine learningMathematics

Related papers

Browse all OTHER papers