
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
Introductory Offer - Only 19 Left
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 DetectionTensorRT 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 ClassesMulti-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.

MobileNetV4 Model
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 Platform
GitHub Repository
Complete source code available on GitHub with comprehensive documentation and examples
Pre-trained AI Models Included
- • YOLOv8 (Optimized)
- • EfficientDet
- • RetinaNet
- • DeepLabV3+
- • U-Net (Lane Detection)
- • Mask R-CNN
- • MonoDepth2
- • Stereo R-CNN
- • DPT (Dense Prediction)
