Pattern recognition structured heuristics methods for image processing in mobile robot navigation

In this project, the main focus is to apply image processing techniques in computer vision through an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods as structured heuristics methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained. ©2010 IEEE.

Development of a support vector machine-based navigation system for driving a mobile robot through paths in plantations

The use of mobile robots turns out to be interesting in activities where the action of human specialist is difficult or dangerous. Mobile robots are often used for the exploration in areas of difficult access, such as rescue operations and space missions, to avoid human experts exposition to risky situations. Mobile robots are also used in agriculture for planting tasks as well as for keeping the application of pesticides within minimal amounts to mitigate environmental pollution. In this paper we present the development of a system to control the navigation of an autonomous mobile robot through tracks in plantations. Track images are used to control robot direction by preprocessing them to extract image features. Such features are then submitted to a support vector machine in order to find out the most appropriate route. The overall goal of the project to which this work is connected is to develop a real time robot control system to be embedded into a hardware platform. In this paper we report the software implementation of a support vector machine, which so far presented around 93% accuracy in predicting the appropriate route. © 2012 IEEE.

Is the environmental policies procedures a barrier to development of inland navigation and port management? A case of study in Brazil

The main objective of this article is to discuss the Brazilian environmental legislation and policies towards the development of navigation and port management. The research illustrated some difficulties faced by the country and make suggestions to overcome it. The construction of the environmental legal framework began in the early 1960s and resulted in a very complex system, as a consequence of policies adopted by the country. Nowadays Brazilian environmental policies are developed in democratic and participative way, although with elevated degree of bureaucracy and lack of integration among the several governmental agencies, which makes the approval of environmental certifications demand several years for new port projects or improvements, which delays the economic development of the country. Efforts have been made to simplify the licensing process. As result of this research two flowchart for environmental licenses of ports installation are shown: The first shows the process until 2009 and the second shows the process nowadays. This become an important issue due the fact that inland navigation is one of the less pollutant modes of transportation, and although, the process of environmental certification was simplified, if compare with 2009, it is still complex and time-consuming, delaying the development of the infrastructure. © 2012 Elsevier Ltd.

Raman Lidar monitors emissions from sugar cane fires in the State of São Paulo: a pilot-project integrating radar, sodar, aerosol and gas observations

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)