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XIAOR GEEK XR-SLAM Lidar Robot Car with HD Camera ROS Robot Tank Car Assembled 12V 2200Mah Golden
Features:
- SLAM lidar smart car ROS robot tank
- Indoor positioning; automatic obstacle avoidance
- Human body tracking and object tracking
- Lidar path planning
- With a camera, line tracking is enabled
- ROS mileage feedback
- XR-Lidar S1 laser scanning ranging radar: adopt OPTMAG optical and magnetic fusion technology. Meet Class 1 laser safety standards. 8m/26.2ft measurement radius; 360-degree scanning ranging; 3860 times/second measurement frequency
- XR-ROS human-computer interaction system easy to use: The robot is equipped with our self-developed XR-ROS Human-Computer Interaction System with exclusive APP, which can realize interactive operations such as real-time mapping or navigation on the mobile phone. Easy to use
- Laser triangulation technology: Through the SLAM algorithm, it can easily scan the building to construct a map (for gmapping, hector/Harto algorithm)
- With a board for Raspberry Pi 4B and a driver board for the ROS robot
- Colorful radar light: 7 rainbow colors and 8 display modes (1 marquee display mode + 7 monochrome display modes)
- Map construction and autonomous navigation: Facilitating the era of human intelligence
- Endurance time: about 30 minutes for 2200mAh battery
Advantages:
- SLAM lidar to build a map: XR-Lidar S1 lidar is used. Support for gmapping, hector/Harto algorithm to build a map. It also supports keyboard, mouse and selection area to build maps
- Indoor automatic obstacle avoidance and indoor positioning: According to the indoor map, it will plan the path. When the road is blocked, it will carry out secondary planning to achieve dynamic obstacle avoidance
- With a camera, it enables line tracking
- Mobile APP to control the robot: provide mobile APP software for Android, complete WIFI video monitoring and control, complete APP map building and autonomous navigation. Control movement, car position setting, navigation target setting and path display through mobile APP
- Real-time display on the touch screen: When you operate the ROS robot, you often need to connect the main control board to WIFI, you need to know the IP address of the main control board in time, and you need to monitor the real-time operation of the main control board. Its touch screen helps you complete the above operations
- SLAM algorithm technology application: The SLAM algorithm learned through the ROS lidar smart car can be applied to the mainstream unmanned automatic delivery robots and household robot cleaners
Construction:
- Robot-Eyes 3rd Generation 1080P HD Camera
- High quality acrylic stand
- 3.5" touch screen
- 9-axis gyroscope
- With original board for Raspberry Pi 4B and XIAOR GEEK driver board
- Large size aluminum alloy body
- XR-Lidar S1 lidar
Specifications:
- ROS robot main control board: XR-ROS PT4
- Body Dimensions: 280 x 242 x 300mm/11 x 9.5 x 11.8"
- Battery: 12V 2200mAh
- Motor: DC brush motor (with 360-line AB code)
- Programming software: Python and C language
- Weight: about 3kg/6.6lb
- Digital display voltage: 3-segment digital display
- IMU: Nine-axis gyro sensor
Package Included:
- 1 x Robot Car
- 1 x 16G Memory Card
- 1 x User Manual
Note:
- It is assembled and ready to use.
Encoder Parameters:
- Type: AB Phase Incremental Magnetic Hall Encoder
- Line speed: base pulse 11 PPR x gear reduction ratio
- Supply voltage: DC 3.3V / DC5.0
- Basic functions: self-contained pull-up shaping resistor, MCU direct connection
- Interface type: PH2.0 (standard cable)
- Output signal type: square wave AB phase
- Response frequency: 100KHz
- Number of base pulses: 11 PPR
- Number of magnetic ring trigger poles: 22 poles (11 pairs of poles)
Gear Motor:
- Model: XR25-370 Hall encoder geared motor
- Motor size: Diameter 25mm (length dimensions vary according to parameters)
- Shaft diameter: 4mm diameter D-shaped shaft
- Output shaft length: 12mm D length 8mm
- Voltage: DC6-24V (can not be mixed, that is, 12V is 12V, can not be used for 24V)
- Weight: about 100g (different reduction ratios and different parameters have different weights)
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Application cases: 2WD intelligent self-balancing cars, intelligent
home appliances, robots, camera arms, electric paper cutters, etc.