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EXAMPLES.md

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Examples of Simulation

This page is generated by generate_example_gallery.py from the demo images under src/simulations and updated automatically after merge. Do not edit it by hand — edit the docstring of the simulation script instead.

Localization

EKF vs UKF vs Particle Filter Comparison

Compares EKF, UKF and Particle Filter localization with the same motion model, GNSS observations and noise
Author: Sahruday Patti

EKF vs UKF Comparison

Compares EKF and UKF localization with GNSS observations
Author: Bruno DOKPOMIWA

Extended Kalman Filter Localization

Estimates the vehicle pose by fusing a motion model and GNSS observations with an Extended Kalman Filter
Author: Shisato Yano

Particle Filter Localization

Estimates the vehicle pose with weighted samples (particles) and GNSS observations
Author: Sahruday Patti

Unscented Kalman Filter Localization

Estimates the vehicle pose with an Unscented Kalman Filter using sigma points and GNSS observations
Author: Bruno DOKPOMIWA

Mapping

Binary Occupancy Grid Map

Builds a grid map that marks each cell as occupied or free from LiDAR point clouds
Author: Shisato Yano, Bhavesh Lokesh Agarwal

Cost Map

Builds a grid map that assigns a cost to each cell from LiDAR point clouds
Author: Bhavesh Lokesh Agarwal

NDT Map

Builds a map of normal distributions (mean and covariance) per grid cell from LiDAR point clouds
Author: Shisato Yano

Potential Field Map

Builds a potential field map from LiDAR point clouds, with high potential around obstacles
Author: Panav Arpit Raaj

VFH Polar Histogram

Builds a polar obstacle density histogram around the vehicle from LiDAR point clouds
Author: Khushi

Path Planning

ACO

Ant Colony Optimization: ants search the grid and reinforce shorter paths with pheromones
Author: Banaan Kiamanesh

Bidirectional A*

Runs A* search from both the start and the goal until the two searches meet
Author: Erwin Lejeune

Hybrid A*

A* search over continuous vehicle poses using motion primitives that respect the minimum turning radius
Author: Shreyansh Shethia

A*

Grid-based shortest path search guided by a heuristic distance to the goal
Author: Shantanu Parab

Dijkstra

Grid-based shortest path search that expands the lowest-cost node first
Author: Ashish Varma

D*

Incremental replanning when a new obstacle appears on the planned path
Author: Erwin Lejeune

Elastic Bands

Smooths an A* path by treating it as an elastic band pushed away from obstacles
Author: Erwin Lejeune

GA

Genetic Algorithm: evolves candidate paths and smooths the best one with a spline
Author: Banaan Kiamanesh

Gradient Descent

Plans a path by descending the gradient of a potential field toward the goal
Author: Panav Arpit Raaj

Informed RRT*

RRT* that samples only inside an ellipse once a first path is found, to converge faster
Author: Rajat Arora

PRM

Samples random nodes, connects them into a roadmap and searches it with Dijkstra
Author: Erwin Lejeune

PSO

Particle Swarm Optimization: a swarm of candidate paths converges toward the best one
Author: Erwin Lejeune

Q-Learning

Learns a Q-table policy on the grid by reinforcement learning and follows its greedy path
Author: Banaan Kiamanesh

RRT

Grows a random tree from the start until it reaches the goal
Author: Shantanu Parab

Bidirectional RRT*

Grows RRT* trees from both the start and the goal and connects them
Author: Erwin Lejeune

RRT*

RRT that rewires the tree to shorten paths as more samples are added
Author: Erwin Lejeune

Path Tracking

Adaptive Pure Pursuit Path Tracking

Pure Pursuit whose look-ahead distance shortens on sharp turns and lengthens on straights
Author: Erwin Lejeune

LQR (Linear Quadratic Regulator) Path Tracking

Steering control that minimizes a quadratic cost of tracking error and control input
Author: Shisato Yano

MPC Path Tracking

Optimizes future inputs over a prediction horizon with do-mpc and shows the predicted trajectory
Author: Mohit Kumar

MPPI Path Tracking

Samples many input sequences, weights them by cost, and shows all evaluated trajectories
Author: Erwin Lejeune

Pure Pursuit Path Tracking

Steers toward a look-ahead point on the course
Author: Shisato Yano

Rear Wheel Feedback Path Tracking

Steering control based on the lateral and heading errors at the rear wheel
Author: Shisato Yano

Stanley Steering Control Path Tracking

Steering control based on the heading error and the lateral error at the front wheel
Author: Shisato Yano

Perception

LiDAR Obstacle Sensing

Simulates an omni-directional LiDAR that detects moving and static obstacles as point clouds
Author: Shisato Yano

Rectangle Fitting Detection

Fits a rectangle to each obstacle's point cloud by L-shape fitting
Fits a rectangle to each obstacle's point cloud by robust least squares
Author: Shisato Yano, Shreyansh Shethia

Point Cloud Nearest Neighbor Search (kd-tree)

Finds the nearest source point for each target point with a kd-tree
Finds all source points within a radius of each target point with a kd-tree
Author: Shisato Yano

Sensor's Extrinsic Parameters Estimation

Estimates the LiDAR's mounting position and angle on the vehicle with an Unscented Kalman Filter
Author: Shisato Yano

Course

Cubic Spline Course

Builds a 2D cubic spline course and computes its yaw angle and curvature
Interpolates sample points with a 1D cubic spline
Author: Shisato Yano