X Inertial-aided Visual Odometry
- vio
- visual-inertial
- odometry
- slam
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X Inertial-aided Visual Odometry
CubeSLAM: Monocular 3D Object Detection and SLAM
The fuse stack provides a general architecture for performing sensor fusion live on a robot. Some possible applications include state estimation, localization, mapping, and calibration.
A new voxel layer leveraging modern 3D graphics tools to modernize navigation environmental representations
Open Robotics Automation Virtual Environment: An environment for testing, developing, and deploying robotics motion planning algorithms.
URDF Loaders for Unity and THREE.js with example ATHLETE URDF Files open sourced from NASA JPL
vibe coded supermimic within 1h, LAFAN passed within 1.5 gpuh training
A lightweight, accurate and robust monocular visual inertial odometry based on Multi-State Constraint Kalman Filter.
Blazing fast hexapod robot simulator for the web.
Precise localization based on GNSS and IMU.
Detect 6-DOF grasp poses in point clouds
Real-Time 3D Semantic Reconstruction from 2D data
[ICRA] Crowd-aware Robot Navigation
OverlapNet - Loop Closing for 3D LiDAR-based SLAM (chen2020rss)
Real time semantic slam in ROS with a hand held RGB-D camera
RBDL is a C++ library that contains some essential and efficient rigid body dynamics algorithms such as the Articulated Body Algorithm (ABA) for forward dynamics, Recursive Newton-Euler Algorithm (RNEA) for inverse dynamics, the Composite Rigid Body Algorithm (CRBA) for the efficient computation of the joint space inertia matrix and is also able to compute forward dynamics with external contact constraints and collision impulses. Furthermore it has some basic support for forward and inverse kinematics.
SolidWorks to URDF Exporter
ROS-based framework and RPi image to control PX4-powered drones 🍀
Dense Visual Odometry and SLAM
Remove then revert (IROS 2020)
This repository contains multiple approaches for generating global racetrajectories.
Pure Pursuit Control and SE(2) Planning
YARP - Yet Another Robot Platform
A ROS node to perform a probabilistic 3-D/6-DOF localization system for mobile robots with 3-D LIDAR(s). It implements pointcloud based Monte Carlo localization that uses a reference pointcloud as a map.