Path tracking with dynamic bicycle models
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Updated
Jun 9, 2020 - Python
Path tracking with dynamic bicycle models
A description of the Kinematic Bicycle Model written in Cython with an animated example.
Supports the various URDF and GAZEBO mobile robot model
A repository of introductory autonomous ground vehicle (i.e., wheeled mobile robot) simulation examples in Python.
Controlling a nonholonomic robot to follow a trajectory with a modified PID Controller.
Given a graph, A* finds the optimal path, if it exists, joining the start node to the goal node. Hybrid A* takes vehicle dynamics into consideration and generates a smoother path which the vehicle can follow. Both the implementations are optimized using dictionaries & heaps
Implementation of DDP algorithm for Optimal Control on a Bicycle Model for optimal lane change maneuvering and Skidpad track following.
Control of a 6-state bicycle model for racing and evading random obstacles utilizing Model Predictive Control (MPC).
Model Predictive Control (MPC) for kinematic bicycle model
Repo for the Bikestream project (aka Databike Pilot Project)
Visualizing path prediction using Bicycle Model for various Initial Velocities, acceleration, steering angle, heading angle and calculation time
Building models that capture vehicle dynamics
Coursera specialization
Real-time algorithms for following a given path while avoiding initially unknown static obstacles.
This repository is created based on the projects opened at the Coursera Self-driving Cars specialization course, published by Toronto University. https://www.coursera.org/specializations/self-driving-cars
Control of Mobile Robots course project 2021/2022 - Politecnico di Milano.
A simple simulation of the bicycle model using Qt.
Bicycle Dynamics - Stability analysis and designing controller for Bicycle. SBU Modern Control course final project.
Bicyle model tests.
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