Carlos Sanoja | Freelancer Resume

CarlosSanoja Master Student at Universidad Simón Bolívar, Venezuela Education birthdate- - nationality Venezuelan contact ELE328 - Laboratorio C Grupo de I+D en Mecatrónica Univ. Simón Bolívar Sartenejas 89000 Miranda, Venezuela Experience 07/2019 _now aiMonkey LLC. Caracas, Venezuela Chief Technology Oﬃcer, CTO • Ensure a safe and engaged workforce and industry leading customer experience, in collaboration with peers, employees and cross-functional teams. • Lead engineering and software development team. Responsible for the success of all New Product Development focused in Business Intelligence. • Responsible for building teams, set scope, schedule and manage the staﬀ and lead development of oﬀerings to meet target cost on various end-to-end software solutions. • Project planning and supervision of customer satisfaction standards. 09/2019 _now JanWay Texas, EEUU Lead Electronics Engineer • Electrical design of the whole system. Model the needs of the product and carry out the corresponding simulations in Multisim to verify its operation. • Design of the ﬁrmware on the ESP32 platform. We worked with functionalities such as integration of sensors and actuators, Bluetooth low energy, OTA and connection through WiFi. It was developed using C++ and FreeRTOS as tools. Udacity Inc California, EEUU Senior Project Reviewer and Mentor of the Robotic Nanodegree Program • Ensure that students receive the best possible feedback on their projects by providing constructive evaluations. • Guide students to improve their projects in the reviews you provide them in a professional yet friendly and positive tone. +58 -- languages Spanish mother tonge Portuguese - Advance English - Advance programming C++, Matlab, Python OpenCV, ROS networks LinkedIn Github Professional Development Robotic Software Engineer C++ Software Engineer Sensor Fusion Engineer Self-Driving Cars Specialization Deep Learning Specialization Publications Design, Modelling, Control and Simulation of Biomimetic Underwater Robot, IEEE LARS Master in Electronic Engineering Universidad Simón Bolívar, Venezuela GPA: 5.0/5.0 Bachelor in Electronic Engineering Universidad Simón Bolívar, Venezuela Modelling and ﬂight control design of a quadcopter robot GPA: 4.0/5.0 10/2018 _now 10/2016 _now Group of research and development in mechatronics Universidad Simón Bolívar, Venezuela Junior Research Assistant • In charge of designing and implementing the sensor fusion for autonomous sailboat presented at World Robotic Sailing Championship. In addition, designed a computer vision pipeline to identify other boats, buoys and tags attached to the sails. • Research in quantiﬁcation of the volume of the hippocampus in the progression of alzheimer’s using deep learning. • Currently working on designing and implementing a computer vision pipeline to improve underwater image contrast, generate 2D mosaics, classiﬁcation and object detection. Professional Development IoT Project Development For this project I made the electrical design, from the conceptual design, electrical simulations using Multisim, to the realization of the schematic and PCB in Altium software. For this project, the system requirements were analyzed, from energy to mechanical design. On the other hand, the system is based on the ESP32 microcontroller with wiﬁ and Bluetooth capabilities. That is why I developed a multitasking program using FreeRTOS and C++ that is capable of performing all the operations that the system requires. It has connectivity with the internet and a serial communication display system was implemented using a 4DGL screen. Robust Control for Spacecraft Rendezvous Based on the dynamic model of relative motion illustrated by C-W equations, it is proposed to address the problem of robust control for a class of spacecraft encounter systems as discussed in Gao, which contain parametric uncertainties, external perturbations and input restrictions. The paper proposes A state feedback controller H∞ designed with a Lyapunov approach, which ensures that the closed-loop system meets the multi-target design requirements. The conditions of existence of the allowable controllers are formulated as liner matrix inequalities (LMI), and the controller design is aﬀected by a convex optimization problem subject to LMI limitations. This paper aims to use some of the development explained above and design a control system that replicates some of its results. Autonomous Sailboat Development For this project the hardware and software was designed with the objective of achieving the autonomous operation of a sailboat. The architecture contemplates the development of the modules of acquisition, perception, planning of movement and control. Speciﬁcally, a camera, a GPS and an IMU were used as the main means to locate the boat and the obstacles. The pipeline was designed for data acquisition, ﬁltering and analysis using ROS on a Raspberry pi 3B+. On the other hand, low level rudder and sail control was implemented in the ESP32 microcontroller. A state machine was implemented to achieve the navigation objectives on the lake and the possibility of remote control of the system was added. Quadcopter Modelling and Control This degree project addresses the development of a control system for a quadcopter. The work starts from a pre-existing model, which is made a review and speciﬁc changes to present a nonlinear model of the vehicle. To perform ﬂight tests and the performance of the controllers, it uses the simulation platform Rotors based on ROS (Robotic Operating System) and develops a new module to properly adjust the dynamic and physical structure to it. Similarly, it presents a nonlinear model of the quadcopter in Simulink to facilitate the task of tuning and obtain references to the behavior of the same prior simulation. To simulate the behavior of the real plant, sensors are simulated and a package is proposed to make the estimation of the states based on the input of them. Finally, the advantages, considerations and selection of PID controllers in cascade are evaluated based on ideal data and estimated taking into account the force required by the body to perform the movements. Parameter Optimization for a 2 Degree Robotic Arm This paper aims to describe the results obtained from the comparison between particle swarm optimization (PSO), Genetic Algorithm (GE) and the empirical selection of the parameters of a 2 degrees of freedom robotic arm controller. Localization & Estimation with Bayesian Filters This project is intended to show the state of the art of Unmanned Aerial Vehicle (UAV) location in environments where there are no GPS trust markers in the computer vision area. To understand how the advances in the generation and interpretation of these markers, have allowed diﬀerent achievements in the area of driving autonomous vehicles, particularly aerial vehicles. Simultaneous Localization and Mapping Project:Map My World A two wheeled robot equipped with a RGB-D camera and a 2D Lidar sensor was designed to traverse two Gazebo world environments while performing Simultaneous Localization and Mapping (SLAM). This work aims to generate 2D occupancy grids and 3D octomaps of the provided environments using Real Time Appearance Based Mapping (RTAB-Map). Deep Reinforcement Learning Arm Manipulation In this project is analyzed the behavior of the control arm using deep reinforcement learning to learn from raw sensor data (to detect collisions) through simulation. Finally, it is shown the eﬀect of hyper-parameters in the Q-Network and the function reward design to successfully teach the arm to control joints to achieve the goal. It is present preliminary results in direct transfer of policies over to a real robot, without any further training.