#SLAM
Simultaneous Localisation and Mapping algorithms, implementations, and hardware.
3D LiDAR SLAM with FAST-LIO2: Real-Time Point Cloud Registration on NVIDIA Jetson Orin Nano
Plan a FAST-LIO2 mapping pipeline on Jetson Orin Nano. Check ROS port compatibility, Livox timestamps, IMU extrinsics, map growth, and performance budgets.
RealSense D435i vs Stereolabs ZED 2i: Visual-Inertial Odometry Comparison and Benchmark Method
Compare RealSense D435i and ZED 2i for visual-inertial odometry. Learn sensing limits, timing, calibration, and a reproducible method for measuring drift.
Configuring ROS 2 Nav2 Costmaps: Inflation, Footprints, and Clearing for Constrained Corridors
Tune ROS 2 Nav2 costmaps for constrained corridors. Define footprints, balance inflation costs, clear ghost obstacles, and validate safe navigation in RViz.
Fusing IMU, Wheel Odometry, and GPS with ROS 2 robot_localization: A Dual EKF Guide
Fuse wheel odometry, IMU, and GPS with robot_localization. Configure dual EKFs, heading conventions, navsat transforms, covariance, and TF ownership.
How to Train a Custom Object Detection Model for Your Robot
A practical guide to collecting training data, labeling images, fine-tuning a detection model, and deploying it to a robot's edge hardware.
ROS 2 for Beginners: Setting Up Your First Project
A gentle introduction to ROS 2 concepts, installation, and getting a first publisher/subscriber project running before diving into Nav2 and SLAM.
Obstacle Avoidance Robot with LiDAR and ROS 2
An intermediate guide to building an autonomous navigating robot using ROS 2, a 2D LiDAR, and the Nav2 stack.
SLAM Explained: How Robots Build Maps and Find Themselves
A technical breakdown of Simultaneous Localization and Mapping (SLAM) algorithms and hardware requirements.
AI for Robotics: The Complete 2026 Guide
An overview of how AI and machine learning are applied in modern robotics, from perception to path planning.