abdabdul Goto Github PK
Type: User
Bio: Software Developer, Model Predictive Control, Kalman Filters, Trajectory Planning and Following, Ego Motion Compensation
abdabdul's Projects
acado
ACADO Toolkit is a software environment and algorithm collection for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control, state and parameter estimation and robust optimization.
adore
Adore project
autoware
Autoware - the world's leading open-source software project for autonomous driving
carla
Open-source simulator for autonomous driving research.
carla-autoware
Integration of AutoWare AV software with the CARLA simulator
carla-ros-bridge
ROS bridge for CARLA Simulator. Goes with fork of Carla simulator.
casadi
CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python or Matlab/Octave.
core_planning
do-mpc
Model predictive control python toolbox
dynamics-and-control
Jupyter notebooks for Dynamics and Control
frenet
Transform Frenet (s,d) to local Cartesian (x,y) coordinates.
kalman
*THIS FORK IS UPDATED REGULARLY* Header-only C++11 Kalman Filtering Library (EKF, UKF) based on Eigen3
mapviz
Modular ROS visualization tool for 2D data.
mapviz-tile-map-google-maps-satellite
ROS Offline Google Maps for MapViz
moveit
:robot: The MoveIt motion planning framework
moveit2
:robot: MoveIt for ROS 2
mpcc
Model Predictive Contouring Controller (MPCC) for Autonomous Racing
navigation.ros.org
https://navigation.ros.org/
omg-tools
Optimal Motion Generation-tools: motion planning made easy
osqp
The Operator Splitting QP Solver
pnguidance
pythonrobotics
Python sample codes for robotics algorithms.
selfdrivingcars
University of Toronto
separating_planes_trajectory
Implementation of the trajectory planning optimisation method presented in the following paper: https://hal.archives-ouvertes.fr/hal-01639745
studio
Robotics visualization and debugging
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