Name: Muhammmad kazim
Type: User
Company: Khalifa University
Bio: Postdoctoral Researcher at Khalifa University, Abu Dhabi, UAE.
My research area is Autonomous vehicles (UAVs and UGVs), Control theory, CV, DL, and DRL.
Location: Abu Dhabi, UAE
Blog: dr-kazim.com
Muhammmad kazim's Projects
Dockerized ROS + Gazebo with GPU support
Using Rosparam to change the location of your target.
Deep learning inference nodes for ROS with support for NVIDIA Jetson TX1/TX2/Xavier and TensorRT
Visualize ROS topics inside a terminal with Unicode/ASCII art
Model Predictive Control for Quadrotors with extension to Perception-Aware MPC
Quadrotor control framework developed by the Robotics and Perception Group
Time-Optimal Planning for Quadrotor Waypoint Flight
PyBullet CartPole and Quadrotor environments—with CasADi symbolic a priori dynamics—for learning-based control and RL
Safe Exploration with MPC and Gaussian process models
Safe reinforcement learning with stability guarantees
Search and Rescue Drone
Resources for deep learning with satellite & aerial imagery
Udacity Self-Driving Car Project 5: Vehicle Detection and Tracking
Udacity Self-Driving Car Engineer Nanodegree projects.
Coursera Open Courses from University of Toronto
This is the setting Up tools for C++ programming on window, Linux and MacOS.
[CVPR2019] Fast Online Object Tracking and Segmentation: A Unifying Approach
We present an effective, easy-to-implement, and low-cost modular framework for completing complex navigation tasks.
A Framework for Zero-Shot Sim2Real Drone Racing
Dynamics | Controller | Trajectory Generator | Path Planner
The main MRS simulation Gazebo/ROS package. Part of the "mrs_uav_system".
The English version of 14 lectures on visual SLAM.
edition 2 of the slambook
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
Sniffy Bug: A fully autonomous swarm of gas-seeking nano quadcopters in cluttered environments
ROS: Zero to ROS course
Multi-modal ROS-based people detection and tracking framework for mobile robots developed within the context of the EU FP7 project SPENCER.