This document is a combination of the SC18 IEEE proceedings format and a modified SC18 artifact descriptor to be used for the HPCSYSPROS18 CFP. More information here: https://github.com/HPCSYSPROS/CFP18
This paper implements Simultaneous Localization and Mapping (SLAM) technique to construct a map of a given environment. A Real Time Appearance Based Mapping (RTAB-Map) approach was taken for accomplishing this task. Initially, a 2d occupancy grid and 3d octomap was created from a provided simulated environment. Next, a personal simulated environment was created for mapping as well. In this appearance based method, a process called Loop Closure is used to determine whether a robot has seen a location before or not. In this paper, it is seen that RTAB-Map is optimized for large scale and long term SLAM by using multiple strategies to allow for loop closure to be done in real time and the results depict that it can be an excellent solution for SLAM to develop robots that can map an environment in both 2d and 3d.
Physics being an experimental science, we sought to learn how to prepare a lab and perform as a team accounting for errors and uncertainties and to reduce them. We gathered values for volume using Micrometer, gathered information on acceleration, velocity, and created a histogram using a PASCO motion sensor. A jumping experiment was also performed with a human and the motion sensor. Our main goal was to test the effects of human error and eliminating mechanical error.
Esta es una plantilla utilizada para la presentación de trabajos prácticos, cuenta con elementos predefinidos y distintas secciones. Originalmente fue diseñana para la cátedra de Simulación de Ingeniería en Sistemas pero se puede utilizar para cualquier otra cátedra
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