Multi Robot Task Allocation For Inspection Problems With Cooperative Tasks Using Hybrid Genetic Algorithms
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Multi-Robot Task Allocation for Inspection Problems with Cooperative Tasks Using Hybrid Genetic Algorithms
In this dissertation, methods for optimal multi-robot task allocation (MRTA) for industrial plant inspection are investigated. MRTA involves distributing and scheduling a set of tasks for a group of robots to minimize the total cost taking into account operational constraints. With technical progress and declining cost of robotic mobility, interest in industrial mobile robotics has grown significantly in recent years. Many efforts have been devoted to mobility-related problems such as self-localization and mapping, though only few studies deal with the optimal task allocation in multi-robot systems. Since a good task allocation provides more efficient scheduling (e.g. less cost, shorter time), the objective of this research is to develop search/optimization methods for inspection problems that involve both single- and two-robot tasks.
Close range 3D thermography: real-time reconstruction of high fidelity 3D thermograms
Author: Antonio Rafael Ordóñez Müller
language: en
Publisher: kassel university press GmbH
Release Date: 2019-01-21
Infrared thermography enables the non-contact measurement of an object’s surface temperature and presents the results in form of thermal images. The analysis of these images provides valuable information about an object’s thermal state. However, the fidelity of the thermal images strongly depends on the pose of the thermographic camera with respect to the surface. 3D thermography offers the possibility to overcome this and other limitations that affect conventional 2D thermography but most 3D thermographic systems developed so far generate 3D thermograms from a single perspective or from few noncontiguous points of view and do not operate in real time. As a result, the 3D thermograms they generate do not offer much advantage over conventional thermal images. However, recent technological advances have unlocked the possibility of implementing affordable handheld 3D thermal imaging systems that can be easily maneuvered around an object and that can generate high-fidelity 3D thermograms in real time. This thesis explores various aspects involved in the real-time generation of high-fidelity 3D thermograms at close range using a handheld 3D thermal imaging system, presents the results of scanning an operating industrial furnace and discusses the problems associated with the generation of 3D thermograms of large objects with complex geometries.
Intelligent Systems
The two-volume set LNAI 12319 and 12320 constitutes the proceedings of the 9th Brazilian Conference on Intelligent Systems, BRACIS 2020, held in Rio Grande, Brazil, in October 2020. The total of 90 papers presented in these two volumes was carefully reviewed and selected from 228 submissions. The contributions are organized in the following topical section: Part I: Evolutionary computation, metaheuristics, constrains and search, combinatorial and numerical optimization; neural networks, deep learning and computer vision; and text mining and natural language processing. Part II: Agent and multi-agent systems, planning and reinforcement learning; knowledge representation, logic and fuzzy systems; machine learning and data mining; and multidisciplinary artificial and computational intelligence and applications. Due to the Corona pandemic BRACIS 2020 was held as a virtual event.