Professional-grade F450 assembled drone DIY kit C++ Pythone secondary development open source flight control

Wheelbase: 450mm (diagonal size of motor) Weight: 1493G (including battery, Raspberry Pi 4b) Flight control: Pixhawk2.4.8 open source flight control Camera: 2 million pixel HD 1080P Indoor hovering: optical flow module, ranging and altitude radar GPS: m8n GPS Battery life: about 20 minutes, no wind at sea level (affected by the environment) Battery: 3S 5200mah (11.1v) Load: 500G Wind resistance: 3-4 breeze Motor: Langyu A2212 ESC: Haoying Letian 20A (supports 3S-4S lithium battery) Propeller: T1045 self-locking propeller Flight distance: 2000 meters (no interference, no obstacles, no obstructions in the area) Flight altitude: 1000 Meters Flight environment: Indoor/outdoor Open source system ：ubuntu20.04 S0C：Broadcom BCM2711 CPU：64-bit 1.5GHz quad-core (28nm process) GPU:Broadcom Videocore Vl@ 500MHz Bluetooth 5.0 USB2.0*2/USB3.0*2 micro HDMI*2 RAM:4GB DDR4 Maximum resolution:Support 4K/1080p 60Hz/2*4k 30Hz Power supply interface:Type C(5V 3A)/micro USB(5V 3A) WIFI: 802.11AC wireless 2.4GHz/5GHz dual-band Wi-Fi Wired network: Gigabit Ethernet (network port accessible) Poe:Power over Ethernet (PoE) via additional HAT The system has turned on the WIFI hotspot (Acopter) Use 4b's WiFi to start the self-built hotspot (ACopter). The PC can directly connect to the 4b's WIFI hotspot to form a local area network and remotely connect to the drone through the SSH command Integrated with data transmission telemetry and image transmission functions It can communicate and transmit images with the computer ground station MP through the WIFI network, without the need for a data transmission module. When the PC is connected to the 4b WIFI hotspot, access 10.42.0.10:3000 through a web browser to enable data transmission and data transmission functions. Dronekit-python control can realize indoor GPS-free positioning and navigation Combined with dronekit-pyhton and opencv, most indoor programming operation missions can be realized Opencv visual processing A monocular camera has been added, which can be used for image transmission and post-processing: the video stream can be read through the Raspberry Pi, and visual processing can be performed using tools such as opencv: the real-time high-definition video stream can also be sent back to the PC for processing, or sent back to the mobile phone for viewing.