VisionSense™

Research & Development Platform

Advanced perception system for autonomous vehicle research with stereo cameras and pre-trained AI models. Built on NVIDIA Jetson Orin Nano with comprehensive AutoVision software stack.

$1,249

$945

Save $304

Limited time offer

Free shipping included • 2-year warranty

Hardware Features

NVIDIA Jetson Orin Nano (8GB)
Stereo Camera Module (1080p@60fps)
Mono Camera Module (4K@30fps)
AutoVision Software Stack
ROS2 Native Integration
TensorRT Optimized Models
Open-source Platform
2-Year Warranty Included

What's Included

• Jetson Orin Nano Development Board
• Stereo Camera Module
• Mono Camera Module
• All Necessary Cables
• Mounting Hardware
• Getting Started Guide
• 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.

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.

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 Recognition

Comprehensive traffic sign detection and classification including speed limits, stop signs, and regulatory signs.

🚥

Traffic Light Detection

Real-time traffic light state detection and classification for intersection navigation.

📏

Depth Estimation

Stereo vision-based depth estimation for 3D scene understanding and obstacle avoidance.

🤖

ROS2 Integration & Packages

Native ROS2 nodes and packages for seamless integration with robotics workflows and autonomous systems.

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)