XiaoQiang XQ4general purpose ROS developing platform

Extraordinary high performance, beyond your imagination

  • Visual Navigation

    Obstacle Recognition

    XiaoQiang can find obstacles easily by using data from RGBD camera. As we can see from the video, XiaoQiang can recognize the obstacles quickly no matter whether it's static or dynamic. Then we can start path planning process after projecting the obstacles into a 2D plane.

  • Real World Tests

    XiaoQiang detects obstacles when a stick is putting in front of it, and then stops immediately. XiaoQiang continues moving forward when the stick is removed.

  • Real Time Visual Navigation

    The ground was placed with random obstacles. XiaoQiang got the infomation of obstacles by using data from RGBD camera. The green curve in the video was XiaoQiang's target path and position. XiaoQiang planning its path in real time based on the situation of obstacles. As we can see from the video, XiaoQiang reaches its goal smoothly even in very complex environment.

  • Navigation Examples

    Inertial Navigation

    Inertial navigation is to use only the data from gyroscope and encoder to navigate. The car moved in a 1M X 1M squal by the control of navigation program in the video. The left part of the video is the real state of the car, and the right part of video is computer simulation of the car in real time.

  • Visual Navigation

    Visual navigation is to use image data from camera to navigate. The left part of the video is the real time video from camera. The right part of the video is the real time position of the car in the map. The green dots is the key points of environment. The green squre represents current position of car. The red curve if the target path of the car. As we can see, XiaoQiang moves smoothly along the red curve.

  • Real Time Navigation

    The ground was placed with random obstacles. XiaoQiang got the infomation of obstacles by using data from RGBD camera. The green curve in the video was XiaoQiang's target path and position. XiaoQiang planning its path in real time based on the situation of obstacles. As we can see from the video, XiaoQiang reaches its goal smoothly even in very complex environment.

  • Remote Control

    Obstacle Recognition

    XiaoQiang can find obstacles easily by using data from RGBD camera. As we can see from the video, XiaoQiang can recognize the obstacles quickly no matter whether it's static or dynamic. Then we can start path planning process after projecting the obstacles into a 2D plane.

  • Real World Tests

    XiaoQiang detects obstacles when a stick is putting in front of it, and then stops immediately. XiaoQiang continues moving forward when the stick is removed.

  • Real Time Visual Navigation

    The ground was placed with random obstacles. XiaoQiang got the infomation of obstacles by using data from RGBD camera. The green curve in the video was XiaoQiang's target path and position. XiaoQiang planning its path in real time based on the situation of obstacles. As we can see from the video, XiaoQiang reaches its goal smoothly even in very complex environment.

Hardware configurations

  • i7-4500U Core Duo processor 1.8GHz CPU Turbo 3.0GHZ
    8G memory
    64G SSD

  • Battery: 12V 20AH, Rated current 5A, Rated power 60W.
    7 hours at high power usage (80% CPU usage)

  • max speed 0.8m/s
    max acceleration 1.5m/s^2
    max angle speed 230 deg/s
    max angle acceleration 660 deg/s^2

  • 6 USB with four USB3.0 and two USB2.0
    60fps 178° camera
    MPU9250 9-axis high-precision gyroscope

Buy XiaoQiang

Extraordinary high performance, beyond your imagination