Intelligent Navigation Laboratory

AIN-X

Jingtian Robot Intelligent Navigation Laboratory is an integrated system that uses unmanned vehicles as a carrier, and is driven by the cross fusion development of artificial intelligence, big data, and the Internet of Things. It intelligently achieves autonomy or collaboration to complete complex tasks. Equipped with TURTLEBOT4 robot, AI artificial intelligence platform, and Jingtian Cloud control software, it can easily achieve functions such as map construction, autonomous navigation, machine learning, unmanned driving, multi-sensor applications, etc. Each module has expansion interfaces and provides open source code to support secondary development to the maximum extent.

Features

Fusion of multimodal perception technology: Chassis Creat@3 Built in anti collision sensors, anti fall sensors, infrared sensors, etc. Configure a 360 degree LiDAR. Configure OAK binocular depth camera, provide AI neural network calculation, up to 4T computing power, achieve object pose estimation, object detection, recognition and tracking, human/gesture recognition, 3D semantic segmentation, feature point tracking, face recognition, etc.

Built in AI Operating System: The AI operating system allows for one click installation and launch of common practical cases on the robot platform. It also includes various mapping and navigation algorithms, as well as additional demo functions such as wall and line patrols.

Support Multiple Algorithm Validations: The Turtlebot 4 swarm robot platform can verify algorithms such as deep learning, machine learning, artificial intelligence, collaborative positioning, area coverage, task planning, resource allocation, communication methods, etc., ensuring the diversity of the experimental platform and allowing for experiments in most disciplines.

Technical index

Technical parameters

Dimensions	341x339x192 mm
Wheel Diameter	72mm
Maximum Rotation Speed	1.90 rad/s
Working Hours	2.5 - 4 hrs(depending on the load)
User Power Supply	VBAT@1.9A(14.4V nominal)，Provides low current 5V and 3.3V through Raspberry Pi GPI0
2D Radar	0.15-12m range, 8kHz sampling rate, 360 ° angle range, 1 ° angle resolution
Software	Ubuntu 22.04, ROS2 Humble system; Supports ROS 1.0 ROS2.0、Gazebo, Rviz

Weight	3.3kg
Obstacle Clearance Height	4.5mm
Maximum Speed	0.31 m/s (safe mode), 0.46 m/s (non safe mode)
Battery	26 Wh lithium-ion, rechargeable
Charging Dock	Automatically dock for charging
Open Interface	USB2.0×2、USB3.0×2
Camera	13 million high pixel RGB camera, global shutter binocular depth camera for measuring distances of 0.2-19.1m

Fittings

Configure a custom platform. Explore all accessories.

AI experimental operation platform

The graphical interface is clear and concise, and can be used for single or multi machine configuration of Turtlebot4. Supports ROS2.0, pre installed with scientific research algorithms such as local and global path planning, and provides sensor corresponding auxiliary functions.

visual remote online control

Real time display of robot simulation control interface, environment perception screen, monitoring full view screen, etc., effectively obtaining real-time image data and GNSS absolute position information.

customized SLAM sand table scene

Simulate indoor and outdoor scene mapping environments, building environments, etc., and can also be combined with optical motion capture systems to complete the validation of multi robot formation control algorithms.

supporting textbooks

The supporting textbook "Autonomous Intelligent Navigation of Robots" was written by Professor Guo Chi of Wuhan University and recommended by Academicians Liu Jingnan and Wang Yaonan.