OAK-D Short Range PoE with ToF

Description

OAK-D SR PoE is a camera that emphasizes improved short-range accuracy when compared to the standard OAK-D and further expands our catalog of robotic vision solutions. It employs Time of Flight (ToF) VGA sensor, which enables accurate measurement of the depth of objects in a scene, resulting in more precise focusing and improved low-light performance.

Specifications:

• IR dot projector
• Time of Flight (ToF) VGA (640x480 @ 30fps)
  
• Two OV9782 (1 MP Color Global Shutter)
• IP67 rated enclosure
  
• M12 X-coded connector
• M8 IO connector
• PoE circuitry

1. Github Repository 

OAK-D SR PoE is the ultimate camera for robotic vision that perceives the world like a human by combining stereo depth camera and high-resolution color camera with an on-device Neural Network inferencing and Computer Vision capabilities. It uses PoE for both power and GigE connectivity.

PoE connection allows cameras to communicate to other computers via networking protocols (TCP, UDP, HTTP, MQTT, etc.). As our PoE models feature device flash memory, you can also run your programs in standalone mode. OAK PoE cameras are housed in an rugged, IP-rated enclosure, which is required for industrial and outdoor use. Furthermore, this OAK camera offers industrial M12 PoE connector (instead of less-industrial RJ45) and an additional M8 connector for IO connectivity (USB2, FSIN, STROBE, 5V/GND, GPIO).
We suggest following Getting started with OAK PoE devices as the first steps after installation.

Main Features:

• 4 TOPS of processing power (1.4 TOPS for AI - RVC2 NN Performance)
• Run any AI model, even custom architectured/built ones (models need to be converted)
• Encoding: H.264, H.265, MJPEG, 4K/30FPS, 1080P/60FPS
• Computer vision: warp (undistortion), resize, crop via ImageManip node, edge detection, feature tracking. You can also run custom CV functions
• Stereo depth perception with filtering, post-processing, RGB-depth alignment, and high configurability
• Object tracking: 2D and 3D tracking with ObjectTracker node

Camera Specifications: