ToF Imager Enables Advanced Obstacle Avoidance and Smart Navigation in Vacuum Cleaning Robot
Dreame has launched its new vacuum cleaning robot, the Dreame Bot W10 Pro. The smart vacuum cleaner is equipped with a camera featuring the REAL3 Time of Flight (ToF) image sensor from Infineon Technologies AG and pmdtechnologies. The ToF imager enables smart navigation, 3D mapping, and excellent obstacle avoidance for service robots, cleaning robots and mops.
“The camera of Dreame's premium robot vacuum cleaner is equipped with our state-of-the-art 3D ToF imager technology. Combined with the latest technology for better contextual awareness from Dreame, the imager enables the cleaning device to identify and avoid obstacles,” said Christian Herzum, Vice President Product-Line 3D-Sensing from Infineon. “Our advanced 3D vision engineering helps service robots learn from their daily cleaning routine and recognize household items that may interfere with floor cleaning, such as cords, shoes, slippers and socks.”
Infineon's 3D ToF imager provides additional distance information for each of the cameras’ 38000 pixels. It offers significantly improved 3D accuracy and precision compared to conventional solutions including single-pixel ToF devices. This high resolution enables 3D camera designs with a large vertical field of view (FoV), allowing robots to detect small objects with high resolution and measure the height of furniture. Without getting stuck, the robot can thus move under the couch, chair, table or other objects, reducing maintenance.
Since pmdtechnologies patented SBI (Suppression of Background Illumination) technology is integrated in each pixel, the cleaning robot can be used in different lighting conditions. As a result, the ToF imager generates robust 3D depth data that allows the room to be imaged in difficult ambient lighting conditions. Even disturbances such as strong sunlight, dim light or materials with different reflection indexes do not affect the repeatability and quality of the measurement.
More information is available here.
