ROS Robot Mecanum Wheel Car Robot Assembled With ORBBEC Depth Camera Host For Raspberry Pi 4B 4GB

ROS Robot Mecanum Wheel Car Robot Assembled With ORBBEC Depth Camera Host For Raspberry Pi 4B 4GB

Features:
- Using SLAM navigation algorithm technology
- DIY food delivery robot, sweeping robot, AGV car, and delivery robot
- Mecanum unmanned educational robot
- Mecanum omnidirectional kinematics, built-in torque suspension, for Raspberry Pi 4B, wireless network card for Intel
- For ROS·BOBOTICS·OPENCV SLAM·TENSOFLOW·CUDA·YOLO
- Laser SLAM/Visual SLAM/Image processing
- Open source all code supporting explanation
- Powerful functions: visual three-dimensional depth mapping, visual SLAM positioning navigation, lidar, grid map, path planning dynamic obstacle avoidance, depth camera video monitoring, color camera visual line inspection, indoor positioning autonomous navigation, mobile app mapping navigation, image Processing, ROS framework odometer deduction, convenient for remote development
- Metal texture, well-designed. Torsional suspension, four-wheel landing (Note: robots made by other producers without suspension cannot land on four wheels at the same time due to mechanical rigidity, and the kinematics data is not accurate. The robots cannot overcome obstacles)
- Can create maps and navigate through computers and mobile phones

Function List:
1. Basic Functions of ROS Robot:
- Robot ROS serial port transparent transmission
- IMU and odometer data feedback
- Motor and battery data feedback
- Robot URDF model
- Multi-sensor data fusion
- RVIZ data visualization
- Graphical debugging of PID parameters
- Rear drive electronic differential
- Three-segment battery display
- Keyboard, handle, app control
- Analysis of automobile trapezoidal steering
- ROS APP mapping navigation

2. SLAM Positioning Map Navigation, Path Planning:
- For Gmapping SLAM mapping
- For Cartographer SLAM
- For Karto SLAM mapping
- For Hector SLAM mapping
- For Cartographer IMU SLAM
- Robot fixed-point navigation
- Robot multi-point cruise
- Robot autonomous obstacle avoidance
- For AMCL Monte Carlo positioning
- Map Navigation for Android APP
- Lidar moving object tracking
- Robot autonomous exploration and mapping
- Robot simultaneous mapping and navigation
- Global path planning algorithm
- TEB local path planner
- For AMCL particle filter positioning

3. RGBD Depth Camera, Visual SLAM:
- For RTABMAP pure visual mapping navigation
- Monocular ORB_SlamV2
- For RTABMAP+Laser mapping navigation
- Monocular + depth ORB_SlamV2
- Robot depth image acquisition
- Robot color image acquisition
- Robot color point cloud acquisition
- Robot depth image acquisition

4. Multi-robot Formation:
- Multi-robot independent control, synchronous control
- Multi-robot distributed communication
- Multi-robot radar navigation
- Synchronous formation of multiple robots

Robot Parameters:
- Robot model: HuanYuBot-H21X04
- Motion model: Mecanum omnidirectional kinematics model
- ROS host: For Raspberry Pi 4B
- Lidar: SLAMTEC A1 Lidar high-speed version
- Depth Camera: Depth Camera for Astra Pro ORBBEC
- Chassis control: STM32F405RGT6
- Battery: 12.6V, 6000maH
- Load description: less than 4kg/8.8 lb
- Voltage display: three-segment LED indication for fuel gauge
- Size: 30 x 23 x 22cm/11.8 x 9.1 x 8.7" (LxWxH)
- Endurance time: 6-8 hours
- Body material: 2.5mm/0.1" oxide sandblasted high-strength aluminum alloy

Parameters for Raspberry Pi 4B 4GB:
- System: for ubuntu 18.08
- Memory: 4G operation, 32G storage
- ROS: for ROS Melodic
- Network: WIFI connection, hotspot can be set
- CPU: Quad-core for ARM Cortex-A72 64-bit 1.5GHZ
- GPU: for Broadcom VideoCore VI 500Mhz
- Deep learning: not supported
- USB: USB2.0*2, USB3.0*2
- Three-dimensional vision: support

SLAMTEC A1 High-speed Lidar:
- Measuring radius: 12m/39.4ft
- Scanning frequency: 16Hz
- Scan time: 62ms
- Power up through its switch. Frequency controlled via the switch
- 16Hz navigation dynamic performance improved

Camera for ORBBEC:
- Depth field of view H 58.4° x V 45.7°
- Working range 0.6-8m/2-26.2ft
- Accuracy: ±3mm/0.1" at 1m/3.3ft
- Higher accuracy. High depth information accuracy, meeting the accuracy requirements of multiple scenes
- Ultra-low power consumption. Less than 2.5W, USB2.0 meets power supply requirements
- UVC is driver-free. Plug and play without installing any drivers
- SDK adapts to multiple platforms. Support for Android, Linux, and Windows
- Easy to install. Rugged and durable, comes with a multi-directional base, tightly connected

Package Included:
- 1 x Set of Robot Car

Note:
- It is assembled and ready to use.