Overview
The SU17 Research Drone is a high-performance quadcopter featuring a 6000mAh battery, MID-360 LiDAR for 3D mapping, quad-camera SLAM system for precise localization, and integrated GPS+GLONASS positioning. With a takeoff weight of 2.3 kg and a payload capacity of 200 g, it offers 21 minutes of flight time in visual positioning mode. Powered by Prometheus software, it supports target recognition, path planning, and autonomous navigation, making it an industry-grade solution for research and innovation.
Hardware Parameters
Aircraft
Parameter | Description |
---|---|
Aircraft Type | Quadcopter |
Takeoff Weight (Approx.) | 2.3 kg (with protective cover and battery) |
Diagonal Distance | 320 mm |
Dimensions | Length: 442 mm, Width: 388 mm, Height: 174 mm (excluding protective cover) |
Maximum Payload | 200 g |
Hovering Flight Time | Approx. 13 min (with hover at 100%, not below 0%), visual positioning: 21 min |
Hovering Accuracy | GPS: Vertical ±1.5 m, Horizontal ±2.0 m |
3D LiDAR SLAM: Vertical ±0.08 m, Horizontal ±0.08 m | |
4-camera visual SLAM: Vertical ±0.05 m, Horizontal ±0.05 m | |
Wind Resistance Level | Level 4 |
Operating Temperature | -10°C to 40°C |
Main MCU Chip | STM32H743 |
IMU | ICM42688/BMI088 |
Barometer | MS5611 |
Compass | QMC5883L |
Interface | USB Type-C |
Onboard Computer
Parameter | Description |
---|---|
Processor | Intel Core i5-8365U |
Memory Capacity | 8GB |
Memory Frequency | LPDDR3@2133MHz |
Storage | 256GB NVMe SSD |
Network Port | Baidu Apollo Ethernet X2, 12V@3A power supply, supports IEEE 1588-2008 (PTP v2) |
Serial Port | TTL Serial Port X2, 5V/3.3V@500mA power supply |
USB | Type-C X2 (1x USB2.0, 1x USB3.0) |
HDMI | HDMI 1.4 |
Power Battery
Parameter | Description |
---|---|
Model | SU17-L |
Battery Type | High-pressure lithium polymer battery |
Rated Voltage | 26.4V (Max), 21V (Min) |
Storage Voltage | 22.8V (Typical) |
Rated Capacity | 6000mAh |
Weight | 680 g |
Dimensions | Length: 85.2 mm, Width: 86.5 mm, Height: 135 mm |
Remote Controller
Parameter | Description |
---|---|
Model | QE-2 |
Channels | 8 |
Transmission Power | 18~20 dBm |
Weight | 294.1 g |
Gimbal
Parameter | Description |
---|---|
Controllable Angle | -90° ~ 30° (Tilt Axis) |
Streaming Protocol | RTSP (Standard) |
Encoding Format | H.264 |
Resolution | 1080P @ 25fps |
Diagonal FOV (D) | 120° |
Vertical FOV (V) | 54° |
Horizontal FOV (H) | 95° |
Image Transmission
Parameter | Description |
---|---|
Operating Frequency | 2.4GHz |
Transmission Power | 18dBm |
Communication Range | 3Km (No Interference, No Obstacle) |
Image Range | 1Km (Minimal Interference, No Obstacle) |
Maximum Bandwidth | 40Mbps |
Quadruple Depth Camera
Parameter | Description |
---|---|
Vision Accelerator | Intel Movidius Myriad X VPU |
Maximum Resolution | 1296x816 |
Maximum Frame Rate | 1280x800 @ 120fps |
Shutter Type | Global Shutter |
Encoding Format | 8/10-bit Single Stream |
FOV | 150° Diagonal FOV, 127.4° Horizontal FOV, 79.7° Vertical FOV |
Number of Sensors | 4 (2 Front + 2 Rear) |
IMU | BMI270 |
GNSS
Parameter | Description |
---|---|
Horizontal Accuracy | 1.5 m CEP (with SBAS) |
Velocity Accuracy | 0.05 m/s |
Operating Mode | GPS + GLONASS + BDS + GALILEO + SBAS + QZSS |
Charger
Parameter | Description |
---|---|
Model | LK150-2640500 |
AC Input Voltage | 100V ~ 240V |
DC Input Voltage | 26.4V |
Weight | 460 g |
Charging Current | 5A |
3D LiDAR
Parameter | Description |
---|---|
Model | MID-360 |
Laser Wavelength | 905 nm |
Measurement Range | 40 m @ 10% Reflectivity |
FOV | Horizontal 360°, Vertical -7° ~ 52° |
Minimum Range | 0.1 m |
Point Frequency | 10 Hz (Typical) |
Point Output | 200,000 points/s |
Data Interface | 100 BASE-TX Ethernet |
Data Synchronization | IEEE 1588-2008 (PTP v2), GPS |
Built-in IMU | ICM40609 |
Power Supply Voltage | 7~27V |
Dimensions | 65 mm (W) x 65 mm (D) x 60 mm (H) |
Weight | 115 g |
Operating Temperature | -20°C ~ 55°C |
Software Parameters
Onboard Computer
Parameter | Description |
---|---|
Model | Intel Core i5-8365U |
System | Ubuntu 20.04 |
Username | amov |
Password | amov |
ROS | noetic |
OpenCV | 4.7.0 |
Visual Positioning System | BSA_SLAM V1 |
Prometheus Software
Parameter | Description |
---|---|
Version | v2.0 |
PrometheusGroundStation System | v1.24.11.27 (Final version based on Wiki release record) |
Details
SU17 Research Edition
Industry-grade quality research drone
- Optional 3D LiDAR: Enables mapping, positioning, and navigation obstacle avoidance.
- Prometheus Autonomous Drone Software: Rich in demos for quick mastery of drone control.
- Industry-grade flight platform: Stable and open, setting a new standard for research drone performance.
Key Features
The SU17 Research Drone Development Platform (referred to as SU17) adopts an integrated design, incorporating flight controllers, onboard computers, quad-camera SLAM modules, cloud cameras, and image transmission modules for high-level integration, significantly enhancing hardware stability and reliability. Equipped with the Prometheus autonomous drone software, the SU17 supports features such as target recognition, tracking, and path planning for various flight control scenarios.
It optionally integrates the MID-360 3D LiDAR, combined with the FAST-LIO algorithm to achieve 3D LiDAR SLAM, offering precise environmental sensing and positioning information. Paired with the EGO-Swarm path planning algorithm, it enables efficient real-time 3D mapping and obstacle avoidance in complex environments.
Prometheus V2 Software System
The development platform is built on the ROS and Prometheus open-source framework, offering rich functionalities and extensive secondary development APIs for efficient reprogramming. It provides access to positioning information, flight modes, battery status, IMU data, and other drone state and sensor data interfaces, along with control interfaces for position, velocity, acceleration, and attitude.
Additionally, it includes usage examples for related APIs. Furthermore, the drone features safety check functions for flight operations (anti-crash), enabling automatic descent under abnormal conditions, reducing the risk of crashes and ensuring a safer development process.
SpireCV Vision Library
The SpireCV Vision Library is a real-time image processing SDK specifically designed for intelligent UAV systems. It provides functionalities such as gimbal and camera control, video storage and streaming, target detection, recognition, and tracking.
This SDK aims to offer high performance, reliability, and a streamlined interface for developers of intelligent UAV systems. With a feature-rich visual processing solution, it enables developers to efficiently implement various complex vision-based applications.
Prometheus Ground Station
The Prometheus Ground Station is a human-drone interaction interface developed based on the Prometheus system, built using Qt technology. It enables rapid replication of the functionalities of the Prometheus system, providing real-time monitoring and 3D visualization of drone status and control data.
Through the ground station, users can execute commands such as one-click takeoff, hover at the current position, landing, and position control. Additionally, the system supports custom function buttons for initiating user-defined scripts or sending custom messages, significantly improving the convenience, efficiency, and scalability of user operations.
Powerful Expansion
Hardware Expansion Ports
-
Serial Port 1
-
Serial Port 2
-
Network Port 1
-
Network Port 2
-
USB Ports:
- USB 3.0 (Compatible with USB 2.0)
- USB 2.0
Hardware Framework
The image illustrates the hardware architecture of the SU17 drone, highlighting the integration of various components for advanced data processing and system control:
-
Cameras (Camera 1-4):
Connected to a VPU (Vision Processing Unit) for front-end preprocessing. -
VPU:
Handles visual data from multiple cameras and forwards it to the processing units. -
CPU (X86) with iGPU and OpenVINO:
Serves as the primary computational unit for backend processing, supporting network-connected expansion capabilities for enhanced computational power. -
ARM Single-Chip Microcontroller:
Interacts with the CPU via a UART interface for additional control functionalities. -
Front-End Pipelining and Camera 5:
Managed by a dedicated ARM processor for further data streamlining.
This framework integrates multiple processing units, supporting real-time image analysis, advanced computational tasks, and seamless communication between hardware components. It ensures efficient handling of complex operations in research and development applications.
Software Framework
The diagram illustrates the software architecture of the SU17 drone, highlighting the integration of various systems for autonomous functionality:
-
BSA_SLAM (Mapping and Localization):
- Provides spatial mapping and positioning data.
- Integrates depth and IMU sensor inputs for accurate environment perception.
-
SpireCV Vision Perception:
- Processes visual data, including object detection, ROI information, and target tracking.
-
User Applications:
- Interfaces for user-driven tasks such as data visualization and command input.
-
Prometheus Motion Planning:
- Handles trajectory planning using position, velocity, and target data.
-
ASDK Autonomous Driving Framework:
- Serves as the central processing layer, managing data flow between sensors, cameras, cloud modules, and external interfaces.
- Supports multiple input/output channels (e.g., network ports, serial ports).
-
MAVROS:
- Communicates with flight control systems (PX4/FMT) for flight state and position control.
-
Cloud Module and Multi-Sync Cameras:
- Integrates cloud-based data for advanced processing.
- Synchronizes visual inputs for high-precision operations.
Blue Lines: Represent decision-making pathways for trajectory planning.
This architecture demonstrates a modular, extensible design, enabling seamless communication between various hardware and software components for robust drone operation.
Intelligent Openness: Integrated UAV System Solution
The diagram presents a comprehensive and open architecture for drone systems, emphasizing modularity and integration across various components:
-
Core Components:
- FMT Open-source Autopilot: Provides reliable flight control based on modular development, supporting diverse environments and data integration.
- PX4 Flight Control System: Ensures stability and supports advanced modular customization.
- SpireCV Vision Perception Platform: Focuses on image processing, including object detection, tracking, and real-time video streaming.
-
Key Frameworks:
- Prometheus Autonomous UAV Platform: Includes multi-drone control, motion planning, collaborative navigation, and real-world simulations.
- BSA_SLAM System: Combines vision-based SLAM and LiDAR-based SLAM for precise positioning and mapping.
- ASDK G/D Ground Station Control Interface: Enables seamless communication between ground stations and UAVs for monitoring and real-time adjustments.
-
Workflow Integration:
- Highlights processes like motion planning, environment mapping, and autonomous navigation.
- Integration with professional ground stations for trajectory control, obstacle avoidance, and real-time data management.
-
Simulation Support:
- Includes a simulation system for autonomous mission testing, UAV control, and component validation.
This system demonstrates a cutting-edge solution for autonomous UAV development, with scalable capabilities for research, application, and testing in diverse scenarios.
the structural components of the SU17 research drone, emphasizing its stability and advanced design. Key features include the MID360 LiDAR for precise mapping, an omnidirectional vision system for comprehensive environmental perception, a single-axis gimbal for stabilized imaging, and a robust 6S battery for extended power. Other essential components include the propeller system, antenna, navigation lights, and a micro SD card slot for data storage. The design integrates cutting-edge hardware, ensuring reliability and high performance for various research applications.