solution of exercises of the book "probabilistic robotics"
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Updated
May 18, 2023 - C++
solution of exercises of the book "probabilistic robotics"
《概率机器人》课后习题详解。Detailed Solutions for exercises of book "Probabilistic Robotics" in both English & Chinese.
Probabilistic line extraction from 2-D range scan
確率ロボティクスのアルゴリズム解説(こちらに最新・もっと正確なバージョンがあります->)
Solutions to assignments of Robot Mapping Course WS 2013/14
Autonomous Occupancy Probability Mapping Mission Robot Code with Webots and ROS2.
Autonomous mobile robotics algorithms.
This ROS2 package aims to demonstrate how the Particle Filter or Monte Carlo Localization is implemented in a real robot in a simulation world.
SLAM system using Total Least Square algorithm to determine the trajectory of a robot moving in a given environment
2D bearing-only SLAM with least squares
Monte Carlo Localization Simulator - Educational Tool for EL2320 Applied Estimation at KTH Stockholm
A solver for motion planning problems
This is a webots project implementing a controller for e-puck robot that localizes itself with particle filter method
Particle Filter Localization for a Differential Drive Robot using LiDAR scans in a 2D Occupancy Grid
EKF Localization Simulator - Educational Tool for EL2320 Applied Estimation at KTH Stockholm
Sketch of low-level/low-resources graphic engine: Occupancy Grid Mapping for robot navigation tasks.
Implementation "learn intrinsic parameter" pseudocode in Probabilistic robotics (Chapter 6.3.2)
A WebGL-based motion planning visualizer
Experimental fastslam algorithm web application.
Simultaneous Localization and Mapping based on Rao-Blackwellized Particle Filter 🗺️
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