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  • Atsushi Sakai
    Atsushi Sakai An autonomous navigation system engineer, and an OSS developer of PythonRobotics and SciPy etc Japanese web page maintainer of NumPy Links
  • Welcome to PythonRobotics’s documentation! - GitHub Pages
    Welcome to PythonRobotics’s documentation! “PythonRobotics” is a Python code collections and textbook (This document) for robotics algorithm, which is developed on GitHub See this section (What is PythonRobotics?) for more details of this project
  • Grid based search — PythonRobotics documentation
    Grid based search Breadth First Search This is a 2D grid based path planning with Breadth first search algorithm In the animation, cyan points are searched nodes
  • Linear–quadratic regulator (LQR) steering control
    The above equations can be used to update the state of the vehicle at each time step Control Model To formulate the state-space representation of the vehicle dynamics as a linear model, the state vector x and control input vector u are defined as follows:
  • Hybrid a star — PythonRobotics documentation
    Hybrid a star This is a simple vehicle model based hybrid A* path planner Code Link PathPlanning HybridAStar hybrid_a_star hybrid_a_star_planning (start, goal, ox, oy, xy_resolution, yaw_resolution) [source] start: start node goal: goal node ox: x position list of Obstacles [m] oy: y position list of Obstacles [m] xy_resolution: grid resolution [m] yaw_resolution: yaw angle resolution [rad]
  • Inverted Pendulum — PythonRobotics documentation
    Inverted Pendulum An inverted pendulum on a cart consists of a mass \(m\) at the top of a pole of length \(l\) pivoted on a horizontally moving base as shown in the adjacent The objective of the control system is to balance the inverted pendulum by applying a force to the cart that the pendulum is attached to
  • Iterative Closest Point (ICP) Matching — PythonRobotics documentation
    Iterative Closest Point (ICP) Matching This is a 2D ICP matching example with singular value decomposition It can calculate a rotation matrix and a translation vector between points to points
  • Histogram filter localization — PythonRobotics documentation
    \(p_t\) is the probability at the time t \(h(z)\) is the observation probability with the observation z \(d\) is the known distance from the RD-ID to the grid center When the d is 3 0, the h(z) distribution is: The observation probability distribution looks a circle when a RF-ID is observed: Step4: Estimate position from probability
  • B-Spline planning — PythonRobotics documentation
    Bspline interpolation planning PathPlanning BSplinePath bspline_path interpolate_b_spline_path() generates a curve that passes through all waypoints This is a simple example of the interpolation planning:





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