VMX-pi transforms your Raspberry Pi into a reliable, real-time Robotics Controller or Vision/Motion Processor with embedded IMU & CAN-bus interface. VMX-pi plus Raspberry Pi can perform both real-time robotic control and higher-layer Robot Position Tracking, Drivetrain path-planning and kinematics-based control – remotely accessed via Ethernet, Wifi or Bluetooth.
VMX-pi also makes a great Vision/Motion Coprocessor, especially when combined with the VMX-rtk Robotics Toolkit. And VMX-pi CAN Bus connectivity provides an easy way to monitor a robot CAN Bus.
Super-charge your robot:
- Switched-mode Power supply for Raspberry Pi and external devices, including under-voltage management and over-current/short-circuit protection
- 30 Digital IOs and 4 Analog Inputs including circuit protection against over-voltage, and locking connectors for many functions
- Digital Communication Interfaces including CAN, SPI, I2C and UART
- navX-technology 9-axis IMU enabling Motion processing features including Field-Oriented Drive, Auto-balance, Auto-rotate to angle, Collision Detection and more
- Network Time Server w/Battery-backed Real-time clock for synchronizing data and logs on distributed networked robot controllers
Additional Key Features:
- Write code directly on VMX-pi: Functions either as a standalone Development System (via Raspberry Pi inputs for keyboard, mouse, HDMI monitor), or can be used with a remote development environment
- Easily connect to sensors: Breakout boards are available for easily connecting to the Sparkfun QWIIC Connect System family of I2C sensors.
Power up with VMX Robotics Toolkit:
VMX Robotics Toolkit (VMX-rtk) Raspberry Pi Software Images add many features including Video Streaming, Vision Processing Libraries, NTP Server, Real-Time Linux (PREEMPT_RT), ROS Kinetic, WPI Network Tables and more:
- Vision processing with multiple cameras via Raspberry Pi-based OpenCV libraries and USB or Raspberry Pi Camera interfaces
- Video streaming and Video capture to SD Card from Raspberry Pi
- Robot Localization via Motion/Vision Processing fusion with sensor fusion packages (e.g., via the ROS robot_pose_ekf package)
- Integration with environment mapping sensors (e.g., stereo cameras & 2D or 3D LIDAR) to implement Simultaneous Localization and Mapping (SLAM) (e.g., via the ROS gmapping package)