917 research outputs found
Cooperative Active Learning based Dual Control for Exploration and Exploitation in Autonomous Search
In this paper, a multi-estimator based computationally efficient algorithm is developed for autonomous search in an unknown environment with an unknown source. Different from the existing approaches that require massive computational power to support nonlinear Bayesian estimation and complex decision-making process, an efficient cooperative active learning based dual control for exploration and exploitation (COAL-DCEE) is developed for source estimation and path planning. Multiple cooperative estimators are deployed for environment learning process, which is helpful to improving the search performance and robustness against noisy measurements. The number of estimators used in COAL-DCEE is much smaller than that of particles required for Bayesian estimation in information-theoretic approaches. Consequently, the computational load is significantly reduced. As an important feature of this study, the convergence and performance of COAL-DCEE are established in relation to the characteristics of sensor noises and turbulence disturbances. Numerical and experimental studies have been carried out to verify the effectiveness of the proposed framework. Compared with existing approaches, COAL-DCEE not only provides convergence guarantee, but also yields comparable search performance using much less computational power
A review of laser scanning for geological and geotechnical applications in underground mining
Laser scanning can provide timely assessments of mine sites despite adverse
challenges in the operational environment. Although there are several published
articles on laser scanning, there is a need to review them in the context of
underground mining applications. To this end, a holistic review of laser
scanning is presented including progress in 3D scanning systems, data
capture/processing techniques and primary applications in underground mines.
Laser scanning technology has advanced significantly in terms of mobility and
mapping, but there are constraints in coherent and consistent data collection
at certain mines due to feature deficiency, dynamics, and environmental
influences such as dust and water. Studies suggest that laser scanning has
matured over the years for change detection, clearance measurements and
structure mapping applications. However, there is scope for improvements in
lithology identification, surface parameter measurements, logistic tracking and
autonomous navigation. Laser scanning has the potential to provide real-time
solutions but the lack of infrastructure in underground mines for data
transfer, geodetic networking and processing capacity remain limiting factors.
Nevertheless, laser scanners are becoming an integral part of mine automation
thanks to their affordability, accuracy and mobility, which should support
their widespread usage in years to come
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