WHEELTEC S300 Intelligent Mobile Robot Chassis Open Source Robot Car Chassis for Collaborative Robot

WHEELTEC S300 Intelligent Mobile Robot Chassis Open Source Robot Car Chassis for Collaborative Robot

Advantages:
- High-precision encoder
- Hub brushless motor
- Independent suspension system
- All-metal housing
- Optional Lebai robotic arm
- Ultrasonic stereoscopic collision avoidance system
- Dual TOF radar
- Dual depth camera
- Hidden light strip
- Support map navigation
- ROS operating system
- Support operating system for FreeRTOS
- Source code schematics are open source

Description:
S300 uses a number of core chassis patents. It is equipped with an independent suspension system and LM3 robotic arm (optional). The robot is able to return to the charging pile on its own to recharge. It is equipped with two Leishen TOF lidar and a complete stereo ultrasonic collision avoidance system, equipped with the Gemini Pro binocular depth camera to maximize hardware performance. At the same time, we also provide customers with open source software and high-value scientific research platforms.

Jetson TX1 Industrial Control Computer (Built-in SSD):
The Jetson TX1 has more than twice the computing power of the Jetson nano and can also share the software ecosystem for NVIDIA.

Compared with ROS main control for Xavier Nx, in actual use, the Jetson TX1 has a slightly slower training speed at the edge end, and there is almost no significant difference in other performance. The Jetson TX1 is cost-effective.

Jetson TX1:
- CPU: For ARM Cortex-A57MPCore 64-bit at 1.73GHz (quad-core)
- GPU: 256-core GPU for NVIDIA Maxwell
- Memory: 4GB 64-bit LPDDR4 Memory
- USB ports: 1*USB 3.0 and 1*Micro USB
- Image Input: MIPI CSI
- Image output: 1*HDMI 2.0
- Video encoding: H.264/H265 (4Kp30)
- Video Decoding: H.264/H265 (4Kp60)
- Onboard storage: 16GB eMMC 5.1 + 64G SSD
- Network interface: 10/100/1000 BASE-T Ethernet
- Number of GPIO pins: 40
- Rated power: 15W
- Power input: DC12~24V+10%
- Size: 128 x 98 x 70mm/5 x 3.9 x 2.8"
- Net weight: 0.93kg/2.1lb

Dual TOF Lidars:
The M10P is a high-end commercial lidar. The S300 is equipped with two M10P lidars, which enable 360° radar detection without dead zones. Its ultra-high sampling rate and accuracy ensure higher obstacle avoidance performance during autonomous navigation.

M10P Serial Port Version:
- Measurement radius: 30m/98.4ft
- Scanning frequency: 12Hz
- Sampling frequency: 20000Hz
- Output: angle and distance
- Angular resolution: 0.22°
- Driven motor type: brushless motor
- 360° scanning ranging: √
- Interface type: serial port
- Radar principle: TOF

Gemini Pro Binocular Depth Camera:
The Gemini Pro is a binocular depth camera. It can meet the needs of outdoor use. Its performance is comparable to imported cameras such as the D435. It is smaller and more delicate, with smaller blind zones.
- Ranging principle: binocular structured light (infrared projection)
- Depth range: 0.5-2.5m/1.6-8.2ft
- Depth resolution: USB3.0: 640x480 at 640fps
- Depth Field of View (FOV): H67.9° x V45.3°
- RGB resolution: USB3.0: 640x480 at 640fps
- RGB field of view (FOV): H71.0° x V56.7°
- Data and power interface: USB3.0 Type C
- Working environment: indoor/outdoor
- Power consumption: < 2.2W
- Safety: Class1 laser

Product Information:
- Item name: Open Source Mobile Robot
- Model: S300
- Chassis drive structure: differential structure
- Wheels: Double active wheels and four driven wheels
- Maximum chassis speed: 2.0m/s
- Chassis dimensions (without the size of robotic arm): 705 x 576 x 290mm/27.8 x 22.7 x 11.4" (LxWxH)
- Maximum load capacity of chassis: 60kg/132.3lb
- Degrees of freedom of robotic arm: 6DOF
- Robot arm working radius: 638mm/25.1"
- Robot arm repeatability: ±0.5mm/±0.02"
- Robot arm end speed: < 2m/s
- Robotic arm gripper load capacity: 1kg/2.2lb
- End-of-arm camera: Gemini Pro camera
- Net weight: without robotic arm: 56kg/123.5lb
- Robot ROS master: Jetson TX1 (default); for Xavier NX (optional)
- Robot control mode: APP, CAN, serial port, etc.
- Open source description: Open source chassis source code, schematics, and 3D models. The robotic arm is not open source, only SDKs and 3D models are provided
- Robot sensors: 2 TOF radars, 2 depth cameras, and 6 ultrasonic sensors
- Battery: 22.2V 20000mAh lithium battery

Attention:
- The version with chassis comes with one depth camera, and the version with robot arm comes with one more depth camera on its robot arm end effector.

Highlights:
- Automatic recharge: Combined with the mapping and navigation function of ROS, the location of the charging pile is marked on the map, and the robot can navigate to the vicinity of the charging pile by itself for docking charging. Charging pile position calibration, robot and charging pile docking method, low battery automatic recharging and other functions have corresponding tutorials
- Dual quality TOF lidars: Two M10P lidars are installed diagonally of the car body. Through data fusion, it enables a 360° perception of the environment and eliminates blind spots
- Stereo ultrasonic blind spot elimination system: Through the six stereo ultrasonic sensors on the front of the chassis, the robot can complete the blinding of the space that cannot be scanned by the radar and avoid the risk of collision
- Innovative independent suspension chassis: With an innovative suspension structure, the chassis can solve core problems such as wheel suspension. Together with the hub motor and silent universal wheels, the overall robot runs smoothly and noiselessly
- Fully open source and support secondary development: The chassis is fully open source, including 3D models, source code, schematics, development manuals, etc., to help you efficiently carry out secondary development

Key Functions (Open source):
Rtabmap vision and lidar 3D mapping and navigation
Support rtab pure visual mapping navigation, and support radar and visual fusion mapping navigation

Classic 2D lidar mapping, navigation, obstacle avoidance
Support for Gmapping, hector, karto, cartographer. Support fixed-point navigation, multi-point navigation, and obstacle avoidance during navigation

ROS QT function of graphical interface
Deploy QT graphical interface to realize one-click ROS function, intuitive feedback of car speed, power and other information

Yolo traffic sign recognition
You can train your own library of deep learning models. Simple autonomous driving is realized through the RGB camera

Yolo object and gesture recognition
Identify everyday objects using common libraries of deep learning models

Ros_tensorflow object detection
Based on tensorFlow, it can realize the recognition of common objects and the recognition of handwritten digits

Deep vision following
The robot follows by recognizing the distance and orientation of the object by the depth camera

KCF target tracking
The following function of the robot is realized by identifying objects with fixed features by the depth camera

AR tag recognition and following
The depth camera recognizes and tracks the attitude of the AR tag, enables the robot to follow through the AR tag, and expands the positioning of the AR tag

RRT independently explores mapping
Use the RRT algorithm to perform the following operations independently: explore mapping, save maps, and return to the starting point of mapping

Web camera surveillance
The robot camera image can be viewed through any browser on the PC side, and remote monitoring can be quickly deployed

RGB camera line following
By following the ground line with the RGB camera and the lidar, automatic obstacle avoidance can be realized during line patrol

Lidar for following
The robot scans nearby obstacles through lidar and selects the nearest object to follow

LiDAR angle shielding
Through SDK optimization, angle shielding can be achieved for all lidars

TEB and DWA path planning
Provide extremely detailed video tutorials to take novices to learn navigation path planning in depth through python mini games

Robot chassis kinematics analysis
Provide kinematic analysis of robot chassis on the market, including Ackerman, differential, track, mecanum wheel, omnidirectional wheel, and 4WD vehicles

The protection circuit of control board
The electrical wiring of the industrial-grade four-layer board is more compliant, the thermistor realizes real-time temperature control monitoring and protection, and the current sampling realizes the over-current protection of stalled motor through hardware detection

Provide ROS APP for mapping and navigation
Support ROS end control through APP, and realize the control, mapping, navigation and other functions of the car

The bottom end provides a powerful parameter control APP
APP for Android and IOS; Support APP parameter adjustment, gravity sensor control, and waveform display

Source-level video tutorials are available:
- Deep learning video tutorial based on autonomous driving sandbox scenario (Chinese and English subtitles): Through the setting of autonomous driving scenarios, the ROS function is projectized and scenario-based, so that the ROS knowledge you learn can be better applied to actual projects
- Moveit Robotic Arm Video Tutorial (English and Chinese subtitles): Reduced code routines, RVIZ visual interface, take you into the world of Moveit robotic arm learning
- ROS SLAM Principles and Algorithms Detailed Video Tutorial (Chinese and English subtitles)
- ROS Basic Video Tutorial (Chinese and English Subtitles)
- STM32 low-level source code and ROS communication video tutorial (Chinese and English subtitles): From the underlying STM32 code parsing to the ROS basic communication framework construction code-level analysis
- ROS-related ubuntu basic tutorial (Chinese and English subtitles): Quickly master ROS-related ubuntu basics, and improve the backup and burning process for Raspberry Pi/Jetson nano
- ROS function development code-level video tutorial (some videos have Chinese and English subtitles): Code analysis of core functions such as ROS mapping and navigation
- ROS Voice and Video Tutorials (Chinese and English subtitles): Provides basic application tutorials and code analysis combining ROS voice and iFlyTek

Software and Hardware Introduction:
A touchscreen and wireless keyboard:
- Equipped with a 14" touchscreen and wireless keyboard. The keyboard's built-in touchpad replaces a mouse and allows you to debug your robot anytime, anywhere

Body power indicator:
- The hidden light strip embellishes the all-metal shell to greatly enhance the robot's aesthetics

With RC remote control:
- Built-in model aircraft remote control interface. After plugging in the model aircraft remote control, you can control the remote control normally

Battery:
- The capacity of the battery is upgraded to 20000mAh. The battery has the safety performance of air transportation, and has multiple protections such as over-discharge, overcharge, short circuit, and over-voltage. It also comes with a protective charger
- Capacity: 22.2V 20000mAh
- Plug: T-type discharge plug
- Discharge performance: 60A continuous discharge
- Dimensions: 155 x 124 x 71mm/6.1 x 4.9 x 2.8"
- Weight: 2.2kg/4.9lb

Main Hardware:
- Laser radar M10P serial port version
- ROS master Jetson TX1 (the one for Xavier Nx is optional)
- RC remote control
- Gemini Pro depth cameras
- WheelBoard C50A
- 14" touch screen

Package Included:
- 1 x Set of S300 robot chassis and control system
- 2 x M10P radars
- 1 x Gemini Pro depth camera
- 6 x Ultrasonic sensors
- 1 x RC remote control
- 1 x Charging pile
- 1 x 20000mAh lithium battery
- 1 x Robot charger
- 1 x Data download cable

Note:
- The robot is able to return to the charging pile on its own to recharge.
- Depth camera is included in the package.
- It is assembled and has been debugged. Therefore, it is ready to use.

C50A Bottom Control Board:
C50A is the bottom control board of the robot. Its overall performance is outstanding. It adopts industrial-grade 4-layer board and provides multiple protection such as over-temperature and over-current, and reserves common robot development interfaces. It is compatible with brushed and brushless motors, reserves ROS interface and is equipped with corresponding SDKs and open source schematics.