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VisionSense Hardware

VisionSense™

ADS/ADAS Researchers, Robotics Labs, Fleet Managers

Advanced perception system with 3 front-facing cameras, IMU and GNSS sensors, ideal for road data collection or infrastructure inspection.

Camera Configuration

AI Processor Options

$994
$795
Save $199

Introductory Offer - Only 19 Left

Free shipping included • 2-year warranty

AI Perception Capabilities

VisionSense™ leverages state-of-the-art deep learning models for comprehensive scene understanding and autonomous driving perception tasks.

🛣️

Lane Detection & Segmentation

Real-time lane boundary detection and drivable area segmentation using advanced computer vision algorithms.

Lane Detection Visualization
CLRerNet SOTA Model
Multilane Detection
Pretrained CLRerNet optimized for TensorRT achieving state-of-the-art performance on CULane benchmark
81.5%
CULane
F1 Score
95%
TuSimple
F1 Score
High Inference SpeedCurve LanesDLA-34 Backbone
TensorRT Acceleration

Optimized for NVIDIA hardware with significant performance improvements over baseline models

🚗

Object Detection & Tracking

Multi-object detection and tracking for vehicles, pedestrians, cyclists, and other road users.

Object Detection Visualization
YOLOv13 SOTA Model
10 Object Classes
Trained on 135k real-world images from urban and rural environments
54%
Nano
mAP@50
65%
Small
mAP@50
71%
Medium
mAP@50
PedestriansCyclistsCarsPickupsTrucksVansBusesTrainsTraffic SignsTraffic Lights
Multi-Object Tracking

BoT-SORT tracker for robust object tracking across frames with state-of-the-art accuracy

🚦

Traffic Sign & Light Recognition

Comprehensive traffic sign detection and classification including speed limits, stop signs, and regulatory signs, plus real-time traffic light state detection for intersection navigation.

Traffic Sign & Light Recognition
MobileNetV4 Model
55 US SignsTraffic Lights
State-of-the-art accuracy with highly efficient inference for real-time traffic sign recognition and traffic light color status detection
98.7%
Sign Detection
Accuracy
99.2%
Light Status
Accuracy
<25ms
Inference
Latency
Speed LimitsStop SignsYield SignsWarning SignsRegulatory SignsConstruction Signs
Batch Processing

Optimized for edge devices with state-of-the-art accuracy and minimal computational overhead, perfect for real-time autonomous driving applications

🤖

ADAS Platform & ROS Integration

Stereo vision-based depth estimation for 3D scene understanding and obstacle avoidance, with native ROS2 nodes and packages for seamless integration with robotics workflows and autonomous systems.

AutoVision 3D ADAS Platform
AutoVision Platform
Open SourceROS2 Native
Complete ADAS development environment with 3D visualization tools and native ROS2 integration for advanced autonomous vehicle research and development.
±1"
Accuracy
@120ft
<10ms
Network
Latency
120°
Front FOV
Coverage
ROS2 Native3D VisualizationSensor FusionReal-time LoggingModular PipelineADAS FrameworkStereo VisionGPU Acceleration
GitHub Repository

Complete source code available on GitHub with comprehensive documentation and examples

Pre-trained AI Models Included

Detection Models
  • • YOLOv8 (Optimized)
  • • EfficientDet
  • • RetinaNet
Segmentation Models
  • • DeepLabV3+
  • • U-Net (Lane Detection)
  • • Mask R-CNN
Depth Estimation
  • • MonoDepth2
  • • Stereo R-CNN
  • • DPT (Dense Prediction)