Journal

In the field of robotics and artificial intelligence, the primary task is to determine the mobile robot’s location, known as ‘Localization.’ Several methods can be used for mobile robot localization, such as the Kalman filter, Grid-based Markov Localization, and the Monte Carlo Localization (Particle filter). The Monte Carlo method or Particle filtering is currently the most popular localization method due to its optimal trade-off between accuracy and robustness. This method involves describing a probabilistic distribution through a sampling process. The map is sampled based on known prior probabilities, and each particle is assigned a weight representing its probability. Through iterations, the estimate pose of the robot accurately converges.

Market arbitrage is a financial strategy that involves taking advantage of pricing discrepancies in different markets. This practice requires an investor to buy and sell assets simultaneously in different markets to benefit from price differentials. The goal of market arbitrage is to generate profit by exploiting inefficiencies in the market. The aim of this is to find some basic discrepancies in certain crypto markets, when passing from one currency to another using their apis, and to see the times when profit is achievable.

This project was an effort from a team of 4 in the development of a methodology for the implementation of ROS with existing lab equipment including the UR5e, and some of the work cells that were available on the Automation and Industrial Manufacturing Lab from Anahuac University. Different simulations were performed with different parameters, sensors, and different data was transmitted. The framework allowed the connection of ROS with the physical Robot and a virtual twin. An extra effort was given in the complete documentation of the whole process for future reference by the lab administrators. Data could be sent and read from the robot using ROS allowing the creation of more complex work cells in the future.

Through the use of a tomography, the aim is to create a three-dimensional model of a jaw, in order to help dentists to be able to perform dental surgeries before carrying them out on real patients, in addition to the creation and analysis of jaw prostheses.

In this project a team of 3 worked in programming a manual flexible workcell using the MRL programming language. By receiving a different input a different output for the Robot was generated. Depending on the previous steps and state only some actions can be done. Upon advancing the manufacturing of the work piece different flags are activated showing a led indicator. The idea of this project was allowing the usage of HMIs in conjunction with a robot.

This is a simulation of a workcell focusing on assembling a piece, made up of a lid and a base. The conveyor bands work in an asynchronous manner, so sensors must be used and programmed to determine the correct time the lid should be picked and placed on the base. A counter of the amount of items assembled is also part of the workcell. The amount of pieces can be limited just by changing a variable in the program, and the process can be stopped in case of an emergency. If no problem arises the process may continue indefinitely. This cell was programmed both with FactoryIO FBD and with the LOGO! FBD.