Simultaneous Localization And Mapping Project (SLAM)

de către ahmednaserokasha
Simultaneous Localization And Mapping Project (SLAM)
Simultaneous Localization And Mapping Project (SLAM)

SLAM Project for localizing and mapping an indoor environment using Robot Operating System (ROS) and Gazebo simulation. The robot model includes : -Skid steering drive controller -Hokuyo laser range finder -Openni Kinect RGBD Camera -IMU sensor Final results consists of 2D and 3D maps of the environment and database of the previous process.

image of username ahmednaserokasha Flag of Egypt Damanhour, Egypt

Despre mine

Greetings, I'm Ahmed. Thank you for visiting my Profile. I have +4 years’ experience in the fields of Robotics, ROS2 , Python, CPP, Electronics, Machine Learning, and Deep Learning. Presently, I am employed as a Robotics and AI Engineer at Trabotyx, a robotics startup focusing on agricultural robotics and delivering accurate weed control solutions for organic farmers. Specifically, I have extensive experience with the following technologies : ----------------------------------------------------------------------------------------- • Robot Operating System (ROS/ ROS2) • Python • C++ • Mapping • Localization • Path Planning • Autonomous Navigation • Computer Vision • RC robots’ systems • Hardware and sensors selection • Raspberry Pi • Jetson Boards( Nano, Xavier) • Deep Learning, Machine Learning solutions. • Object Detection • Data Featurization Extra skills : --------------- • Scikit-learn, Pandas, NumPy • Web Scraping • Data Exploration, Data cleaning, and bias analysis • SQLite3 databases • PCB Design Hardware and sensors experience : ------------------------------------------- • Cameras( Pi camera, ZED1/ ZED2 camera, Thermal imaging) • IMUs (Accelerometers, Gyros, Magnetometers) • Distance sensing ( IR, Ultrasonic, Proximity ) • LIDAR sensing • GPS modules • Motor drivers • Stepper Motors • Servo Motors Recent Projects: -------------------- • Implemented a visual servoing controller in CPP based on literature techniques • Developed a crop line detection based on Adaptive-ROI methods and implemented with Python • Building a compatible Navigation2 Three-Point-Turn controller • Constructed a robot mission management system using [login to view URL] and integrated it with ROS2 • Implemented autonomous navigation system for outdoor agricultural robots using Navigation2 & ROS2 • Building my robot platform for autonomous indoor navigation tasks and object Detection using ROS & Navigation stack. • Developed a 4WD robot for indoor autonomous or manual navigation using ROS, SLAM, LIDAR, move-base, Gazebo, and Raspberry Pi with added temperature and humidity sensors • Incorporated YOLOv3 /YOLOv5 into various robot platforms • Optimize GoPiGo Robot using ROS and distance sensors to allow the robot to autonomously navigate its environment while avoiding obstacles. • Integrating many AI capabilities like object detection, voice commands, and TTS into a robot platform. • Constructed a cheap bump detection and localization device using GPS, IMU, and ROS • Developed a DNN using NumPy with options for optimization, activation functions, layer number, loss functions, and regularization techniques such as Dropout and L2 regularization. • Created an accident detection algorithm using accelerometer data based on literature benchmarking methods • Conducted digital data processing, filtering, and visualization, and created an ML model for PPG signal to measure blood pressure and detect anxiety

USD35 USD/oră

13 păreri
4.1

Tag-uri