Experimental Validation of Entropy-Driven Swarm Exploration under Sparsity Constraints with Sparse Bayesian Learning

Increasing the autonomy of multi-agent systems or swarms for exploration missions requires tools for efficient information gathering. This work studies this problem from theoretical and experimental perspectives and evaluates an exploration system for multiple ground robots that cooperatively explore a stationary spatial process. For the distributed model, two conceptually different distribution paradigms are considered. The exploration is based on fusing distributively gathered information using Sparse Bayesian Learning (SBL), which permits representing the spatial process in a compressed manner and thus reduces the model complexity and communication load required for the exploration. An entropy-based exploration criterion is formulated to guide the agents. This criterion uses an estimation of a covariance matrix of the model parameters, which is then quantitatively characterized using a D-optimality criterion. The new sampling locations for the agents are then selected to minimize this criterion. To this end, a distributed optimization of the D-optimality criterion is derived. The proposed entropy-driven exploration is then presented from a system perspective and validated in laboratory experiments with two ground robots. The experiments show that SBL together with the distributed entropy-driven exploration is real-time capable and leads to a better performance with respect to time and accuracy compared with similar state-of-the-art algorithms.     

Perturbative theory and modeling of electronic-resonance-enhanced coherent anti-Stokes Raman scattering spectroscopy of nitric oxide

A theory is developed for three-laser electronic-resonance-enhanced (ERE) coherent anti-Stokes Raman scattering (CARS) spectroscopy of nitric oxide (NO). A vibrational Q-branch Raman polarization is excited in the NO molecule by the frequency difference between visible Raman pump and Stokes beams. An ultraviolet probe beam is scattered from the induced Raman polarization to produce an ultraviolet ERE-CARS signal. The frequency of the ultraviolet probe beam is selected to be in electronic resonance with rotational transitions in the A (2)Sigma(+)<--X (2)Pi (1,0) band of NO. This choice results in a resonance between the frequency of the ERE-CARS signal and transitions in the (0,0) band. The theoretical model for ERE-CARS NO spectra has been developed in the perturbative limit. Comparisons to experimental spectra are presented where either the probe laser was scanned with fixed Stokes frequency or the Stokes laser was scanned with fixed probe frequency. At atmospheric pressure and an NO concentration of 100 ppm, good agreement is found between theoretical and experimental spectral peak locations and relative intensities for both types of spectra. Factors relating to saturation in the experiments are discussed, including implications for the theoretical predictions.     

Measurement of nitric oxide concentrations in flames by using electronic-resonance-enhanced coherent anti-Stokes Raman scattering

We have measured nitric oxide (NO) concentrations in flames by using electronic-resonance-enhanced coherent anti-Stokes Raman spectroscopy (ERE-CARS). Visible pump and Stokes beams were tuned to a Q-branch vibrational Raman resonance of NO. A UV probe beam was tuned into resonance with specific rotational transitions in the (v"=1,v'=0) vibrational band in the A(2)Sigma(+)-X(2)Pi electronic transition, thus providing a substantial electronic-resonance enhancement of the resulting CARS signal. NO concentrations were measured at levels down to 50 parts in 10(6) in H(2)/air flames at atmospheric pressure. NO was also detected in heavily sooting C(2)H(2)/air flames at atmospheric pressure with minimal background interference.     

Planning for optimal expansion of leased line communication networks

We report a new heuristic algorithm useful for developing least-cost expansion plans for leased telecommunications networks in which there is a hierarchy of possible transmission facilities. The problem combines network topology design and capacity expansion problems. Implemented on a PC, the algorithm has successfully developed topology growth plans for twenty periods on networks with up to 31 nodes.     

The J = 5 level in S at 5.689 MeV

A polarization-direction correlation measurement at two angles, θ_γ = 60° and 90°, has resulted in an unambiguious spin assignment of J^π, 5⁻ for the 5.69 MeV level of ³⁴S.