Luxonis OAK-D Pro Camera w/ Auto-focus & IP66 Enclosure

Name: Luxonis OAK-D Pro Camera w/ Auto-focus &amp; IP66 Enclosure
Brand: Luxonis
SKU: IOWC-0199
Price: 62999.00 INR
Availability: OutOfStock

₹62,999.00 (Inclusive of all taxes)

Out of Stock

The Luxonis OAK-D Pro is a spatial AI and depth perception camera designed for embedded vision systems, featuring an auto-focus 12MP RGB sensor, active stereo IR for enhanced depth mapping, and integrated night vision for low-light operation, powered and controlled via USB.

Features

Active stereo IR depth sensing for reliable 3D mapping on low-texture surfaces and in low-light conditions.
12MP auto-focus RGB camera (IMX378 sensor) with dynamic focus from 8cm to infinity for sharp close-range imaging.
Integrated 940nm IR LEDs enable night vision functionality for 24/7 operation in robotics and automation.
Rugged IP66-rated enclosure protects the camera for demanding indoor and outdoor industrial environments.
Unified USB-C interface provides both power and high-speed data transfer for simplified system integration.

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Description

The OAK-D Pro Camera from Luxonis is a high-performance spatial AI platform engineered for robotics, automation, and embedded computer vision. It combines a 12MP auto-focus RGB camera with active stereo infrared depth sensing to generate dense, accurate 3D point clouds, even on surfaces with minimal visual texture. The integrated 940nm IR projector and paired monochrome cameras enable robust depth perception in complete darkness, making it suitable for 24/7 operational scenarios.

Housed in a rugged IP66 enclosure, the camera is built to withstand harsh environmental conditions. Its unified USB-C connection simplifies deployment by handling both power delivery and high-bandwidth data transfer for video streams, depth maps, and on-device neural network inference results, streamlining integration into larger systems.

Key Features

Active Stereo IR Depth Sensing: Projects an IR pattern to enhance depth accuracy on textureless surfaces and in low-light environments.
Auto-Focus RGB Imaging: 12MP IMX378 sensor with dynamic focus adjustment from 8cm to infinity for versatile object detection.
Integrated Night Vision: Built-in 940nm IR LEDs provide illumination for depth and grayscale imaging in no-light conditions.
Ruggedized IP66 Enclosure: Dust-tight and protected against powerful water jets for reliable use in industrial and outdoor settings.
On-Device AI Processing: Leverages the Myriad X VPU for running neural networks directly on the camera, reducing host system load.
Unified USB Interface: Single USB-C cable delivers power and facilitates high-speed data transfer for video, depth, and metadata.

Applications

Robotics and Autonomous Navigation: For obstacle avoidance, SLAM, and environmental mapping.
Industrial Automation: Bin picking, quality inspection, and robotic guidance in variable lighting.
Smart Security and Surveillance: People counting, intrusion detection, and perimeter monitoring with depth data.
Augmented and Virtual Reality (AR/VR): Spatial mapping and environment understanding for immersive experiences.
Retail Analytics: Customer behavior tracking and inventory management using 3D vision.

Technical Specifications

Camera Model	OAK-D Pro
Primary RGB Sensor	12MP Sony IMX378 (Auto-Focus)
Depth Sensing Technology	Active Stereo IR (940nm)
RGB Focus Range	8 cm to ∞
Frame Rate	Up to 60 FPS
Spectral Range	Visible + 940nm IR
Shutter Type	Rolling Shutter
Enclosure Rating	IP66
Interface	USB-C (Power & Data)
Dimensions (LxWxH)	150 x 75 x ~35 mm
Weight	230 g

Frequently Asked Questions

What software frameworks are compatible with the OAK-D Pro camera?

The OAK-D Pro is primarily programmed using Luxonis's open-source DepthAI API, which supports Python and C++ bindings. This framework provides high-level access to synchronized RGB video, depth maps, and on-device neural network inference. It integrates seamlessly with popular computer vision libraries like OpenCV and can be used on platforms including Raspberry Pi, NVIDIA Jetson, and standard Linux, Windows, or macOS hosts. The API handles camera calibration, stereo rectification, and point cloud generation, simplifying development for spatial AI applications.

How do I power and connect the OAK-D Pro to my host system?

The camera is powered and communicates data through its single USB-C port. Use the provided locking USB-C cable to connect it directly to a host computer or single-board computer. The host USB port must supply adequate power (typically 5V). For extended cable runs or specific industrial setups, you may require an active USB cable or hub. The camera enumerates as a standard USB video device (UVC) and a serial communication port for control, making it plug-and-play after the DepthAI software stack is installed on your host system.

What is the effective depth sensing range and accuracy of the OAK-D Pro?

Depth performance depends on the resolution mode. At 800p resolution, the minimum detectable distance (MinZ) is approximately 70 cm, while at 400p extended mode, it can perceive objects as close as ~20 cm. Accuracy is typically within a few percent of the measured distance under good conditions. The active IR projector significantly improves depth data quality on low-texture surfaces like blank walls. For optimal results, ensure the target scene is within the camera's field of view and that there is no excessive ambient IR interference from sources like direct sunlight.

Can the OAK-D Pro's integrated AI processor run custom neural networks?

Yes, the onboard Intel Myriad X Vision Processing Unit (VPU) can execute custom convolutional neural networks that have been compiled into a compatible format (OpenVINO IR). Using the DepthAI API, you can deploy models for object detection, segmentation, or classification directly on the camera. This offloads processing from the host CPU, enabling real-time AI on edge devices with lower power consumption. The model conversion and compilation process is documented in Luxonis's resources, supporting frameworks like TensorFlow and PyTorch via OpenVINO's model optimizer.