• Xiaoqiang XQ4-PRO general purpose ROS developing platform

    Extraordinary high performance, beyond your imagination

    i7-5500U 8G 64G SSD
    LIDAR RGBD Mono Camera

  • BW-DR01 High perfomance hub motor driver, special designed for robots

    Dual output, surging power

    Dual output 540W ROS

  • Galileo navigation systemVision and LIDAR fusion positioning navigation system

    Accurate localization, quick response

    Real time positioning Dynamic barrier avoidance path planning

Xiaoqiang

  • real-time map and location of lidar

    When Xiaoqiang is equipped with the laser radar, it can make environment mapping and robot navigation easy and quick. In the use of LIDAR, the robot is required to provide more accurate odometer information. Xiaoqiang's odometer is fused with a gyroscope and encoder, with high accuracy. From this video, As we can see that in a large range (200mx400m) the map built by Xiaoqiang is still very accurate.

  • Visual Navigation

    Xiaoqiang uses the camera to collect the ambient image and uses its powerful computational ability to identify the 3D structure of the environment. The red and green dots in the video are the environmental feature points that it recognize. The map in the lower left corner of the video is its identified environment. As we can see that Xiaoqiang can run the Visual Slam program smoothly, and provide very accurate positioning information.

  • RGBD Barrier Avoidance

    Obstacles are randomly placed on the ground. Xiaoqiang obtains the information of the obstacle through the depth camera. The green curve in the video is the target line and location of Xiaoqiang. Xiaoqiang planning its path in real time according to the situation of obstacles. That is, the blue curve in the video. It can be seen that even in a very complex obstacle environment, Xiaoqiang can move smoothly to the target position.

Xiaoqiang is a general purpose ROS develping platform. It has powerful computational power, long battery endurance and the nimble movement ability. Xiaoqiang is very suitable for developmenting the Ros navigation and the computer vision algorithm. Xiaoqiang has four-wheeled structure, the front two active wheels, and two omni-directional wheels on the back. Such a structure can guarantee the accuracy of the turning angle. The wheel used the rubber material which is not easy to skid to ensure the accuracy and stability of the movement again. Xiaoqiang's main controller is a i7 processor mini computer, contains 8G memory and 64G solid-state drives. This hardware configuration guarantees the strong compute ability of the Xiaoqiang. The battery is 12V 20AH lithium polymer battery, which can be guaranteed to be used for seven hours continuously.

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Hub motor driver

  • High Speed

    The Bluewhale hub motor driver can drive the hub motor rotates at high-speed. In this video, XQ5 which uses this driver was rotating at high-speed.

  • Strong Power

    Bluewhale Hub motor driver, maximum power 1080W, single 540W. The tank in the video is driven by this driver and it's powerful and unstoppable.

  • Liear Motion

    The car in the video is driven by Bluewhale hub motor driver. From the video we can see that the car runs stable at high speed.

The Bluewhale drive controls motor speed with error less than 1%. Maximum power of the driver is 1080W (single 540W). Support operating voltage from 12V to 36V (support lithium battery). Our performance is better than other drives on the market especially in low-speed conditions. We also provide ROS driver for this drive. This allows you to control motor motion directly in ROS. This drive also provides 9-axis gyroscope data, odometer data which makes it easy to continue develop of ROS-related navigation programs. And the driver can be equipped with an optional infrared sensor and ultrasonic sensor. Bluewhale drive is the preferred solution for robotics development.

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Galileo navigation system

  • Navigation Example

    Visual navigation is to use the image data received by the camera to navigate. The left side of the video is the image captured in real time by the camera. The right-hand side is displaying position of the car in the visual map in the real time. The green dots in the image represent the feature points of the obstructions. The green box is the current position of the car. The red curve is the target trajectory of Xiaoqiang. It can be seen that the Xiaoqiang can move stabily along the red curve.

  • Night Test With Light

    Galileo navigation system, as long as the use of visual navigation. So the light in the dark at night need to think of the use of complementary light. In this video we tested two ways to fill the light. One is the infra-red light, one is the visible light to fill, have achieved good results.

  • Galileo Client Navigation Demo

    This video shows the usage Galileo system. The red and green dots in the upper right image of the video are the feature points identified by the Galileo navigation system. The map on the lower left is a map created by Galileo. The triangle icon on the map marks the position of the current robot. Through the client we can control the robot to move to a specific target point.

The Galileo system is a solution for robot positioning and navigation. It uses a variety of sensor fusion to locate, with high precision and good stability. Compared with the traditional positioning method, the Galileo navigation system does not need the user to lay the track, easy to use and low maintenance cost.

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Auto Charging

  • Auto Charging

    Auto Charging

    The Bluewhale automatic charging module uses the infrared signal of the charging dock to locate, and automatic charge the robot. User only needs to place the charging dock in a corner, and fix the charging module in the proper position of the robot. When user sends a signal to the robot through a program to start charging, the robot will move automatically to the charging dock and begin charging.

The Bluewhale automatic charging module uses the infrared signal of the charging dock to locate, and automatic charge the robot. User only needs to place the charging dock in a corner, and fix the charging module in the proper position of the robot. When user sends a signal to the robot through a program to start charging, the robot will move automatically to the charging dock and begin charging.

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