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Autonomous SLAM Drone

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Autonomous SLAM Drone

Advanced GPS-denied navigation with real-time object detection powered by Pixhawk, Intel RealSense, and edge AI processing.

Explore Technology

Key Features

Real-Time VIO SLAM

Precise indoor/outdoor navigation using Intel RealSense D435i depth vision and PX4 VIO with visual-inertial odometry.

VINS-Fusion ORB-SLAM3

Hybrid Localization

Robust positioning through sensor fusion of UWB, TF-Mini-S LiDAR, IMU, and optical flow data.

MAVROS EKF2

Onboard Object Detection

Real-time obstacle identification with YOLOv8 running on Raspberry Pi 5 + Coral TPU accelerator.

TensorFlow Lite OpenCV

Technical Specifications

Component Model Key Features
Flight Controller Pixhawk 2.4.8 PX4 firmware, EKF2 sensor fusion, MAVLink protocol
Depth Camera Intel RealSense D435i 1280×720 @30fps, integrated IMU, global shutter
LiDAR Altimeter TF-Mini-S 12m range, 100Hz update rate, ±10cm accuracy
Edge Computer Raspberry Pi 5 (8GB) Coral USB TPU for AI acceleration, ROS 2 Humble
Power System 3S LiPo 5000mAh High-C rating (50C), smart voltage monitoring

Applications

Search & Rescue

Autonomous exploration of collapsed buildings with victim detection.

Industrial Inspection

GPS-denied infrastructure assessment with crack/defect identification.

Precision Agriculture

Indoor greenhouse monitoring with plant health analysis.

Ready to Integrate Autonomous Navigation?

Our SLAM drone platform is available for research partnerships and commercial deployments.

Request Technical Details

Software Stack

Core Framework

PX4 Flight Stack with MAVROS bridge to ROS 2

PX4 v1.14 ROS 2 Humble

Navigation

VINS-Fusion with UWB integration

VIO EKF2

Computer Vision

YOLOv8s with TensorFlow Lite for edge deployment

OpenCV PyTorch

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