Innovation
R & D Platform- CHRIS LAB
R & D Platform- CHRIS LAB
Located in Beijing Yizhuang Economic Development Zone, CHRIS LAB (Creative Human-Robot Intelligent System Laboratory) is mainly engaged in the technical research of robot-related visual positioning and navigation, machine learning, image monitoring, recognition, and segmentation, as well as a complete set of commercial and industrial logistics distribution solutions.
R & D team
R & D team
The research center has maintained in-depth cooperation with many domestic and foreign universities, including Peking University, Hamburg University in Germany, Carnegie Mellon University in the United States, etc. We have also established overseas research centers in the United States and Germany that have leading algorithm research capabilities.
Research fields
Research fields
In terms of fundamental research, the laboratory focuses on the visual planning and navigation algorithms, robotic systems, chip technology, speech recognition, natural language processing and machine learning.
robot system
robot system
positioning and navigation algorithm
positioning and navigation algorithm
Chip
Chip
Leading SLAM technology
Leading SLAM technology
In combination with the core algorithm, the SLAM technology is to make the plane map three-dimensional by using the camera and lidar module on the robot.Compared with laser navigation technology, the added vision allows the robot to obtain more information and predict the behavior of moving objects more accurately. The robot can “see” and avoid obstacles by setting movement route autonomously based on the acquired information. The applications of this technology include mobile robots, robotic vacuum cleaners,logistics robot and intelligent driving. The innovative human-robot intelligent system laboratory developed by our company focuses on SLAM (Simultaneous Localization and Mapping) technology.
Water tank and related technology
Water tank and related technology
A water tank is installed on the robotic vacuum cleaner to provide wet mopping function, significantly improving product performance and user experience, as well as the product’s market competitiveness.
Regional division technology
Regional division technology
Depending on the room structure, the robotic vacuum cleaner can automatically divide cleaning areas to improve cleaning efficiency.
Switch between sweeping and vacuuming
Switch between sweeping and vacuuming
The robotic vacuum cleaner can automatically identify the roller brush or suction port components and work in the corresponding cleaning mode, which is beneficial to enhance product competitiveness and user experience.
Lidar lifting structure
Lidar lifting structure
The lidar in this technology stretches out when the robotic vacuum cleaner is in use, and retracts when it stops working. The sensor can accurately scan the environment and build a map without compromising the nimble movement of robot beneath the furniture, and also improve the efficiency of cleaning difficult corners.
Video correction technology
The data of visual sensor are used to correct the inertial navigation system and improve the positioning accuracy of robotic vacuum cleaner as well as the mapping accuracy.
Video correction technology
Path planning technology
Path planning technology
Optimize the cleaning of corners when the robot works in the Zig-zag mode, and improve the robot's ability to clean and move out of the corner.