Munir Jojo-Verge (munirjojoverge)

munirjojoverge

Geek Repo

Company:Neo Cybernetica

Location:Washington DC

Home Page:https://www.linkedin.com/in/munirjojoverge/

Twitter:@munirjojoverge

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Munir Jojo-Verge's repositories

Self-Driving-Vehicle-Control-Using-Carla

In this project I implement a controller for the CARLA simulator. The goal was to control the vehicle to follow a race track by navigating through preset waypoints (x,y,speed). The vehicle needs to reach these waypoints at certain desired speeds, so both longitudinal and lateral control was required.

Data-Structures-and-Algorithms-Specialization

Coursera Specialisation Offered By UNIVERSITY OF CALIFORNIA SAN DIEGO NATIONAL RESEARCH UNIVERSITY HIGHER SCHOOL OF ECONOMICS

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rl_AD_urban_baselines

Reinforcement Learning Baselines (OpenAI) applied to Autonomous Driving

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SmartGPT

Chain-of-thought prompt + Flaws & Faulty Logic Reflexion + Resolution

Robotic_Localization_Challenge

In this challenge, you will write a feature-based localization engine to estimate the position of a mobile robot on a computer simulated 2D soccer field. This challenge is inspired by the international RoboCup competition, where teams of autonomous robots play against each other in the game of soccer. We will evaluate your solution based on accuracy, code quality, and how clearly you describe your technique.

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Algorithms-and-Data-Structures

6 Courses from the University of California, San Diego National Research University Higher School of Economics

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apollo

An open autonomous driving platform

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Camera-and-LIDAR-Calibration-and-Visualization-in-ROS

Camera-and-LIDAR-Calibration-and-Visualization-in-ROS

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Deep-Reinforcement-Learning-P2-Continuous-Control

Deep Reinforcement Learning Nano-degree - Udacity: Continuous Control: Reacher

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Deep-Reinforcement-Learning-P3-Multi-agent-Collaboration-and-Competition

Deep Reinforcement Learning P3 Multi-agent Collaboration and Competition

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pdf_summarize_chatGPT

This Python project is designed to summarize PDF documents using OpenAI's GPT-3 AI model.

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RoboND_AMCL_ROS

Adaptive Monte Carlo Localization (AMCL) in ROS

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RoboND_Go_Chase_It

Udacity Nanodegree: Robotics Software Engineer. Project 02: Go Chase It!

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RoboND_RTAB_MAP_ROS

RTAB-Map (Real-Time Appearance-Based Mapping) is a popular solution for SLAM to develop robots that can map environments in 3D. RTAB-Map has good speed and memory management, and it provides custom developed tools for information analysis. Most importantly, the quality of the documentation on ROS Wiki (http://wiki.ros.org/rtabmap_ros) is very high. Being able to leverage RTAB-Map with your own robots will lead to a solid foundation for mapping and localization.

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v-jepa

PyTorch code and models for V-JEPA self-supervised learning from video.

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