ROS SLAM visual robot

———    —

Lidar mapping and navigation | Depth camera machine vision

Path planning with dynamic obstacle avoidance | 3D mapping and navigation

Product Introduction

———    —

XROSTANK is an educational robot developed based on the ROS operating system. It utilizes a Raspberry Pi development board as the main controller and is equipped with high-performance hardware such as a LiDAR, depth camera, and high-performance magnetic encoder motor. It can be used for development and learning in areas such as robot mapping and navigation, path planning, motion control, autonomous driving, and 3D vision.

XROSTANK not only better meets users' learning needs for composite robots, but also provides a rapid development and integration solution for ROS. It offers technical documentation covering robot usage instructions and secondary development guidance, helping you quickly master ROS robots.

                ROS operating system                           Machine vision             Lidar mapping and navigation      3D real-scene mapping

               Autonomous driving                Dynamic Obstacle Avoidance        Multi-point navigation         APP one-click image creation

         Four-wheel independent drive        Omnidirectional movement                     OpenCV                     Python/C++ programming

ROS (Robot Operating System)

———    —

Global mainstream robot communication framework

ROS (Robot Operating System) is an open-source meta-operating system for robots. It provides services similar to those of an operating system, including hardware abstraction description, low-level driver management, execution of common functions, inter-process message passing, and program distribution package management. Its main goal is to provide support for code reuse in robot research and development

ROS   =   Communication mechanism   +   Development tools   +   Application Functionality   +   Ecosystem

①Lidar mapping and navigation

It can develop SLAM algorithms such as Gmapping, Karto, and Hector for map building, and supports path planning, fixed-point navigation, navigation, and multi-point navigation.

② Multi-point navigation with dynamic obstacle avoidance

Lidar can detect the surrounding environment in real-time, dynamically avoid obstacles during navigation, and replan the path upon detecting obstacles.

③ RTAB SLAM 3D visual mapping and navigation

Utilizing the RTAB SLAM algorithm, a 3D color map is constructed by fusing visual and radar data. The robot can navigate and avoid obstacles autonomously within the map, and supports global re-localization and autonomous localization functions.

④ Depth image data point cloud image

Through the corresponding API, depth images, color images, and point cloud data of the camera can be obtained.

ROS Human-Computer Interaction System

———    —

The robot is equipped with the self-developed "XR-ROS Human-Robot Interaction System" and the exclusive "ROSXRMaster" app, which enables real-time mapping or navigation and other interactive functions on the mobile phone side. There is no need for complex operations such as using the command line during use, and even without any coding background, it can be easily used

Specifications

———    —

① 7-inch HDMI display screen      ② Depth camera        ③ Raspberry Pi development board         ④LIDAR S1 radar

⑤ McNamara wheel      ⑥ Large-capacity battery         ⑦ Electric motor           ⑧ Driver board

Depth camera

Real-time video transmission

———    —

The robot, capable of secondary development for visual recognition and visual SLAM, features RGBD depth and deep learning capabilities

Laser scanning ranging radar

———    —

OPTMAG optical-magnetic fusion

*Meets Class 1 laser safety standards

Measurement range within a radius of 08 meters          360° scanning and ranging             Measurement frequency: 3860 times/second

Four-wheel-drive McNaughton wheel chassis

———    —

The chassis and body are constructed using aluminum alloy metal processing, with abundant sensor expansion holes reserved. Complemented by high-precision DC motors and mecanum wheels as the propulsion structure, it can flexibly achieve omnidirectional movement of the robot.

Product Parameters

———    —

Inventory list

———    —

           Raspberry Pi-based Wheeled Robot with Radar                                   Charger                                                   Special storage box

Our services

———    —

Our goal is to continuously improve our own technical capabilities and place greater emphasis on the customer's product experience.