THROBOT ARM
ROS Vision Robot
Laser SLAM mapping navigation/Visual SLAM mapping navigation/Path planning/Dynamic obstacle avoidance/AI machine vision/Moveit! robotic arm
Product Features
Rich in features, fun and easy to use
ROS operating system An open-source meta operating system with a comprehensive ecosystem and user base | LiDAR Can meet the development of ROS SLAM functions such as mapping navigation and path planning | 3D real scene mapping Can be combined with depth cameras to achieve 3D mapping |
APP mapping navigation SLAM mapping and navigation can be performed using the APP | Moveit！ robotic arm Integrating inverse kinematics algorithms for flexible and efficient spatial clampin | Python programming Mainstream programming languages with numerous developer communities |
Jetson Nano Jetson Nano has strong performance support, running faster and smoother | OpenCV Mainstream machine vision frameworks that can meet the needs of most vision related artificial intelligence projects | Mapping and Navigation Built in mapping and navigation algorithm package, autonomous obstacle avoidance during navigation process |
Moveit!
Moveit! kinematics
Moveit! It is currently a professional software for controlling the movement of robotic arms. It integrates the latest achievements in motion planning, control, 3D perception, kinematics, control, and navigation, providing an easy-to-use platform for developing advanced robot applications. It provides a design and integrated evaluation system for new robot products in industrial, commercial, and research and development fields. At present, Moveit! Widely used open-source software has been applied to over 65 robot platforms
Dynamic Interaction
Dynamic interaction between robotic arm and camera
Move_group communicates with the robot through ROStopics and actions to obtain the robot's status (position, nodes, etc.), obtain point cloud or other sensor data, and then transmit it to the robot controller
① Joint status information | ② Transform information |
③ Scene planning | ④ Scalability capability |
⑤ Programmable robotic arm | ⑥ Two degree of freedom camera gimbal |
Kinematic grasping
ROS+robotic arm
Kinematic visual grasping
The kinematics plugin can be used for kinematics, and one can also write their own inverse kinematics algorithm, which can be used in conjunction with a camera to achieve visual grasping of objects and other functions
XR-ROS Human Computer Interaction System
The robot is equipped with a self-developed "XR-ROS Human Computer Interaction System" and the "ROS-SLAM Robot" APP, which can achieve real-time interactive operations such as mapping or navigation on the mobile phone. Even without programming foundation, it can be easily used
① PID closed-loop speed compensation ② Power display
Jetson Nano
AI performance significantly improves, image to video transmission becomes smoother
CPU | GPU |
Full-size large body
Large and domineering tracked chassis body,
Excellent obstacle crossing performance; Quick detachable design with good expandability.
A1 robotic arm A2 robotic arm
RGB camera (with gimbal) 1080P resolution RGB camera paired with a two degree of freedom gimbal can rotate up, down, left, right, and achieve AI visual functions for various scenes | Depth camera Depth cameras can not only achieve the AI visual function of RGB cameras, but also realize advanced gameplay such as depth image data processing, 3D visual mapping and navigation |
(Golden aluminum alloy chassis) (Blue aluminum alloy chassis) (Black aluminum alloy chassis)
ROS Robot Operating System
Global mainstream robot communication framework
ROS (Robot Operating System) is an open-source meta level operating system designed for robots. Provides services similar to operating systems, including hardware abstraction description, low-level driver management, execution of shared functions, inter program message passing, and program distribution package management. Its main goal is to provide code reuse support for robot research and development.
ROS = Communication mechanism + Development tools + Application Functionality + Ecosystem
Laser SLAM mapping and navigation
The robot is equipped with a laser radar, which can achieve laser SLAM functions such as mapping navigation, path planning, dynamic obstacle avoidance, and synchronous positioning through real-time scanning of the surrounding environment 360 °. You can also develop AI functions that meet your needs and enjoy the fun of more technology!
① Lidar mapping and navigation Supports mapping algorithms such as Gmapping, Karto, Hector, as well as path planning, fixed-point navigation, and multi-point navigation. | ② Multi point navigation dynamic obstacle avoidance Lidar can detect the surrounding environment in real time, dynamically avoid obstacles during navigation, and re plan the path after detecting obstacles. |
Visual SLAM mapping and navigation
(Depth Camera Package)
Robots can optionally be equipped with depth cameras, which can not only achieve all AI visual functions of RGB cameras, but also develop more depth vision functions such as depth image data processing and RTAB 3D visual mapping
① RTABSLAM 3D Visual Mapping and Navigation Using the RTAB SLAM algorithm, a 3D color map is constructed by integrating visual and radar data. The robot can autonomously navigate and avoid obstacles in the map, and supports global repositioning and autonomous positioning functions. | ② Depth image data point cloud image Through the corresponding API, depth images, color images, and point cloud data of the camera can be obtained. |
③ AI Visual Recognition Function Gameplay
The head can be equipped with an optional RGB camera or depth camera, using an integrated machine vision library to freely develop AI visual functions
face recognition Using the Cascade Classifier algorithm, faces will be quickly recognized when they appear within the field of view | edge detection Robots can output real-time edge detection results through various detection algorithms | Aruco Augmented Reality Support dynamic detection and tracking of QR code AR tags, which can obtain the posture and coordinates of QR code tags | gesture control Real time gesture detection can be achieved through Opencv, and ROS robots can be controlled to perform corresponding actions |
KCF target tracking Image based KCF correlation filtering algorithm can select any object in the image and achieve target following | touch screen operation 7-inch touch screen for real-time control and easy-to-use ROS robot user interaction system | Visual patrol line Support custom color selection, robots can automatically recognize colors and move forward | color recognition Supporting multiple color options, the ROS robot head will track objects of corresponding colors in real-time. |
Diverse control methods
Supports a variety of control methods (mobile phone, PC). The mobile phone can watch real-time first person video footage of the robot and quickly switch between various functions of the robot, such as Leida mapping and navigation, without the need for complex code operations. The PC side can cooperate with the virtual machine development environment we provide to achieve high-end SLAM functions such as mapping and navigation.
Mobile control Computer control
Experience AI gameplay at lightning speed
It can quickly switch between ROS robot function modes, such as radar mapping, navigation, robotic arm, visual inspection, face detection, recognition and other creative AI gameplay, providing a fast experience of AI gameplay.
Gift materials
Provide robot supporting materials
Paper based introductory learning materials/basic knowledge can also be easily mastered
The materials include (main materials/assembly videos/guidance videos/code analysis/development source code)
Specifications
① Depth camera/RGB camera | ⑤ Nine axis gyroscope sensor |
② 7-inch display screen | ⑥ Large size aluminum alloy body |
③ Jetson Nano motherboard&self-developed driver board | ⑦ Rplidar Al radar |
④ Four degree of freedom robotic arm |
Product Name | JETSON NANO ROS SLAM Vision Robot | ||
Programming software | Python / C++ | ROS version | ROS Melodic |
IMU | Nine axis gyroscope sensor | Virtual machine | Ubuntu 18.04 |
Camera | RGB camera (1080P)/depth camera (Astra Pro) | Network card | intel8265 |
Robotic arm | A1 four degree of freedom robotic arm/A2 four degree of freedom robotic arm | Size | 310*240*360mm |
Display screen | 7-inch 1080 high-definition touch screen (capacitive screen) | Grab weight | ≤200g |
Battery | 8400mAh with charging protection carp battery 12V/8A | Net weight | About 3100g |
Motor | DC brushed motor (with built-in 360 wire AB code) | Battery life | ≤120min |
Communication method | USB/WIFI/wired | Communication method | USB/WIFI/wired |
Shipping List
Product List Display
Depth camera: RGB camera:
Our services
About express delivery | Gift materials | Technical Support |
Our goal is to continuously improve our own technical capabilities and place greater emphasis on the customer's product experience.
