Suchergebnisse für "waveshare OR jetson OR nano OR development OR kit OR lite"

Lernen Sie, wie Sie den ESP32-Mikrocontroller und die MicroPython-Programmierung in Ihren zukünftigen Projekten einsetzen können! Das Projektbuch – geschrieben von Dogan Ibrahim – enthält viele Software- und Hardware-basierte Projekte, die speziell für das MakePython ESP32 Development Kit entwickelt wurden. Das Kit wird mit verschiedenen LEDs, Sensoren und Aktoren geliefert. Ziel des Kits ist es, grundlegende Kenntnisse für die Erstellung von IoT-Projekten zu erwerben. Die in diesem Buch vorgestellten Projekte sind umfassend getestet und funktionsfähig und verwenden alle mitgelieferten Komponenten. Für jedes Projekt gibt es im Buch ein Blockdiagramm, einen Schaltplan, ein vollständiges Programmlisting und eine komplette Programmbeschreibung. Lieferumfang des Kits 1x MakePython ESP32-Entwicklungsboard mit LCD 1x Ultraschall-Entfernungsmodul 1x Temperatur- und Feuchtigkeitssensor 1x Buzzer-Modul 1x DS18B20-Modul 1x Infrarotmodul 1x Potentiometer 1x WS2812-Modul 1x Schallsensor 1x Vibrationssensor 1x Lichtempfindliches Widerstandsmodul 1x Pulssensor 1x Servomotor 1x USB-Kabel 2x Taste 2x Steckplatine 45x Schaltdraht 10x Widerstand 330R 10x LED (Rot) 10x LED (Grün) 1x Projektbuch (Deutsch, 213 Seiten) 46 Projekte im Buch LED-Projekte Blinkende LED Blinkendes SOS Blinkende LED – mit einem Timer Abwechselnd blinkende LEDs Tastersteuerung Ändern der LED-Blinkrate durch Taster-Interrupts Laufschrift-LEDs Binär zählende LEDs Weihnachtsbeleuchtung (zufällig blinkende 8 LEDs) Elektronischer Würfel Glücklicher Tag der Woche Pulsweitenmodulation (PWM) Projekte Erzeugt eine 1000-Hz-PWM-Wellenform mit 50% Tastverhältnis Steuerung der LED-Helligkeit Messung der Frequenz und des Tastverhältnisses einer PWM-Wellenform Melodie-Macher Einfache elektronische Orgel Steuerung eines Servomotors Servomotor DS18B20 Thermometer Analog-Digital-Wandler (ADC) Projekte Spannungsmesser Aufzeichnung der analogen Eingangsspannung ESP32 interner Temperatursensor Ohmmeter Lichtempfindliches Widerstandsmodul Digital-Analog-Wandler (DAC) Projekte Erzeugung von Festspannungen Erzeugen eines Sägezahnsignals Erzeugen eines Dreieckssignals Arbiträre periodische Wellenform Generierung eines Sinussignals Erzeugung eines genauen Sinussignals mit Hilfe von Timer-Interrupts Verwendung des OLED-Displays Sekundenzähler Ereigniszähler DS18B20 OLED-basiertes Digitalthermometer ON-OFF Temperaturregler Messung der Temperatur und Luftfeuchtigkeit Ultraschall-Entfernungsmessung Höhe einer Person (Stadiometer) Messung der Herzfrequenz (Puls) Andere mit dem Kit gelieferte Sensoren Alarm bei Diebstahl Tonaktiviertes Licht Infrarot-Hindernisvermeidung mit Summton WS2812 RGB-LED-Ring Zeitstempel für Temperatur- und Luftfeuchtigkeitswerte Netzwerk-Programmierung WLAN-Scanner Fernsteuerung über den Internetbrowser (mit einem Smartphone oder PC) – Webserver Speichern von Temperatur- und Luftfeuchtigkeitsdaten in der Cloud Low-Power-Betrieb Aufwecken des Prozessors mit einem Timer

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Dieser mehrachsige Roboter bringt Leistung und Größe perfekt in Einklang. Features 5 Achsen Nutzlast: 3 kg Reichweite: 700 mm Wiederholgenauigkeit: 0,1 mm Maximale Geschwindigkeit 1000 mm/s Anwendungen Maschinenwartung Bin Picking Mobile Plattform Laborautomatisierung Roboterforschung Langlebige kollaborative Roboter für Ihre Automatisierung Harmonische Antriebe und Servomotoren in Industriequalität garantieren einen ununterbrochenen Betrieb rund um die Uhr. Hergestellt aus Kohlefaser, 15 kg Gewicht ermöglichen einen einfacheren Einsatz. Flexible Bereitstellung mit sicherer Funktion Handprogrammierung, leicht, platzsparend und einfach für mehrere Anwendungen einsetzbar, ohne Ihr Produktionslayout zu ändern. Perfekt für wiederkehrende Aufgaben. Kollisionserkennung ist für alle unsere Cobots verfügbar. Ihre Sicherheit hat immer oberste Priorität. Grafische Oberfläche für einsteigerfreundliche Programmierung Kompatibel mit verschiedenen Betriebssystemen, einschließlich macOS und Windows. Webbasierte Technologie, kompatibel mit allen gängigen Browsern. Drag & Drop, um Ihren Code in wenigen Minuten zu erstellen. Leistungsstarkes und Open-Source-SDK immer zur Hand Das voll funktionsfähige Open-Source-Python/C++-SDK bietet eine flexiblere Programmierung. ROS/ROS2-Pakete sind einsatzbereit. Beispielcodes helfen Ihnen, den Roboterarm reibungslos einzusetzen. Technische Daten UFactory 850 xArm 5 xArm 6 xArm 7 Nutzlast 5 kg 3 kg 5 kg 3,5 kg Reichweite 850 mm 700 mm 700 mm 700 mm Freiheitsgrade 6 5 6 7 Wiederholbarkeit ±0,02 mm ±0,1 mm ±0,1 mm ±0,1 mm Maximale Geschwindigkeit 1 m/s 1 m/s 1 m/s 1 m/s Gewicht (nur Roboterarm) 20 kg 11,2 kg 12,2 kg 13,7 kg Maximale Geschwindigkeit 180°/s 180°/s 180°/s 180°/s Joint 1 ±360° ±360° ±360° ±360° Joint 2 -132°～132° -118°～120° -118°～120° -118°～120° Joint 3 -242°~3.5° -225°~11° -225°~11° ±360° Joint 4 ±360° -97°~180° ±360° -11°～225° Joint 5 -124°~124° ±360° -97°~180° ±360° Joint 6 ±360° ±360° -97°~180° Joint 7 ±360° Hardware Umgebungstemperaturbereich 0-50°C Stromverbrauch Min. 8,4 W, typisch 200 W, max. 400 W Eingangsstromversorgung 24 V DC, 16,5 A Fußabdruck Ø 126 mm Materialien Aluminium, Kohlefaser Basis-Connector-Typ M5x5 Reinraum der ISO-Klasse 5 Robotermontage Alle Endeffektor-Kommunikationsprotokoll Modbus RTU(rs485) Endeffektor-E/A 2x DI/2x DO/2x AI/1x RS485 Kommunikationsmodus Ethernet Lieferumfang 1x xArm 5 Roboterarm 1x AC-Steuerbox 1x Roboterarm-Stromkabel 1x Roboterarm-Endeffektor-Adapterkabel 1x Roboterarm-Signalkabel 1x Steuerbox-Stromkabel 1x Netzwerkkabel 1x Montagewerkzeug 1x Kurzanleitung

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TurtleBot 4 ist die nächste Generation der weltweit beliebtesten Open-Source-Robotikplattform für Bildung und Forschung und bietet bessere Rechenleistung, bessere Sensoren und ein erstklassiges Benutzererlebnis zu einem erschwinglichen Preis. TurtleBot 4 Lite ist mit einer mobilen iRobot Create 3-Basis, einem leistungsstarken Raspberry Pi 4 mit ROS 2, einer räumlichen KI-Stereokamera OAK-D, 2D LiDAR und mehr ausgestattet. Alle Komponenten wurden nahtlos integriert, um eine sofort einsatzbereite Entwicklungs- und Lernplattform zu bieten. Technische Daten Basisplattform iRobot Create 3 Räder (Durchmesser) 72 mm Bodenfreiheit 4,5 mm Bordcomputer Raspberry Pi 4 (4 GB) Maximale Lineargeschwindigkeit 0,31 m/s im abgesicherten Modus0,46 m/s ohne abgesicherten Modus Maximale Winkelgeschwindigkeit 1,90 rad/s Maximale Nutzlast 9kg Betriebszeit 2h 30m – 4h je nach Belastung Ladezeit 2h 30m Lidar RPLIDAR A1M8 Kamera OAK-D-Lite Benutzerleistung VBAT @1,9 A5 V @ Schwachstrom3,3 V @ Schwachstrom USB-Erweiterung 2x USB 2.0 (Typ A)2x USB 3.0 (Typ A) Programmierbare LEDs Erstelle 3 Lichtringe Tasten und Schalter 2x Create 3 User Buttons1x Create 3 Power Button Batterie 26 Wh Lithium-Ionen (14,4 V nominal) Ladestation Inbegriffen Größe (L x B x H) 342 x 339 x 192 mm Gewicht 3,3 kg Downloads User Manual

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Get Cracking with the Arduino Nano V3, Nano Every, and Nano 33 IoT The seven chapters in this book serve as the first step for novices and microcontroller enthusiasts wishing to make a head start in Arduino programming. The first chapter introduces the Arduino platform, ecosystem, and existing varieties of Arduino Nano boards. It also teaches how to install various tools needed to get started with Arduino Programming. The second chapter kicks off with electronic circuit building and programming around your Arduino. The third chapter explores various buses and analog inputs. In the fourth chapter, you get acquainted with the concept of pulse width modulation (PWM) and working with unipolar stepper motors. In the fifth chapter, you are sure to learn about creating beautiful graphics and basic but useful animation with the aid of an external display. The sixth chapter introduces the readers to the concept of I/O devices such as sensors and the piezo buzzer, exploring their methods of interfacing and programming with the Arduino Nano. The last chapter explores another member of Arduino Nano family, Arduino Nano 33 IoT with its highly interesting capabilities. This chapter employs and deepens many concepts learned from previous chapters to create interesting applications for the vast world of the Internet of Things. The entire book follows a step-by-step approach to explain concepts and the operation of things. Each concept is invariably followed by a to-the-point circuit diagram and code examples. Next come detailed explanations of the syntax and the logic used. By closely following the concepts, you will become comfortable with circuit building, Arduino programming, the workings of the code examples, and the circuit diagrams presented. The book also has plenty of references to external resources wherever needed. An archive file (.zip) comprising the software examples and Fritzing-style circuit diagrams discussed in the book may be downloaded free of charge below.

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Build your own AI microcontroller applications from scratch The MAX78000FTHR from Maxim Integrated is a small development board based on the MAX78000 MCU. The main usage of this board is in artificial intelligence applications (AI) which generally require large amounts of processing power and memory. It marries an Arm Cortex-M4 processor with a floating-point unit (FPU), convolutional neural network (CNN) accelerator, and RISC-V core into a single device. It is designed for ultra-low power consumption, making it ideal for many portable AI-based applications. This book is project-based and aims to teach the basic features of the MAX78000FTHR. It demonstrates how it can be used in various classical and AI-based projects. Each project is described in detail and complete program listings are provided. Readers should be able to use the projects as they are, or modify them to suit their applications. This book covers the following features of the MAX78000FTHR microcontroller development board: Onboard LEDs and buttons External LEDs and buttons Using analog-to-digital converters I²C projects SPI projects UART projects External interrupts and timer interrupts Using the onboard microphone Using the onboard camera Convolutional Neural Network

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Build your own AI microcontroller applications from scratch The MAX78000FTHR from Maxim Integrated is a small development board based on the MAX78000 MCU. The main usage of this board is in artificial intelligence applications (AI) which generally require large amounts of processing power and memory. It marries an Arm Cortex-M4 processor with a floating-point unit (FPU), convolutional neural network (CNN) accelerator, and RISC-V core into a single device. It is designed for ultra-low power consumption, making it ideal for many portable AI-based applications. This book is project-based and aims to teach the basic features of the MAX78000FTHR. It demonstrates how it can be used in various classical and AI-based projects. Each project is described in detail and complete program listings are provided. Readers should be able to use the projects as they are, or modify them to suit their applications. This book covers the following features of the MAX78000FTHR microcontroller development board: Onboard LEDs and buttons External LEDs and buttons Using analog-to-digital converters I²C projects SPI projects UART projects External interrupts and timer interrupts Using the onboard microphone Using the onboard camera Convolutional Neural Network

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For Raspberry Pi, ESP32 and nRF52 with Python, Arduino and Zephyr Bluetooth Low Energy (BLE) radio chips are ubiquitous from Raspberry Pi to light bulbs. BLE is an elaborate technology with a comprehensive specification, but the basics are quite accessible. A progressive and systematic approach will lead you far in mastering this wireless communication technique, which is essential for working in low power scenarios. In this book, you’ll learn how to: Discover BLE devices in the neighborhood by listening to their advertisements. Create your own BLE devices advertising data. Connect to BLE devices such as heart rate monitors and proximity reporters. Create secure connections to BLE devices with encryption and authentication. Understand BLE service and profile specifications and implement them. Reverse engineer a BLE device with a proprietary implementation and control it with your own software. Make your BLE devices use as little power as possible. This book shows you the ropes of BLE programming with Python and the Bleak library on a Raspberry Pi or PC, with C++ and NimBLE-Arduino on Espressif’s ESP32 development boards, and with C on one of the development boards supported by the Zephyr real-time operating system, such as Nordic Semiconductor's nRF52 boards. Starting with a very little amount of theory, you’ll develop code right from the beginning. After you’ve completed this book, you’ll know enough to create your own BLE applications.

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For Raspberry Pi, ESP32 and nRF52 with Python, Arduino and Zephyr Bluetooth Low Energy (BLE) radio chips are ubiquitous from Raspberry Pi to light bulbs. BLE is an elaborate technology with a comprehensive specification, but the basics are quite accessible. A progressive and systematic approach will lead you far in mastering this wireless communication technique, which is essential for working in low power scenarios. In this book, you’ll learn how to: Discover BLE devices in the neighborhood by listening to their advertisements. Create your own BLE devices advertising data. Connect to BLE devices such as heart rate monitors and proximity reporters. Create secure connections to BLE devices with encryption and authentication. Understand BLE service and profile specifications and implement them. Reverse engineer a BLE device with a proprietary implementation and control it with your own software. Make your BLE devices use as little power as possible. This book shows you the ropes of BLE programming with Python and the Bleak library on a Raspberry Pi or PC, with C++ and NimBLE-Arduino on Espressif’s ESP32 development boards, and with C on one of the development boards supported by the Zephyr real-time operating system, such as Nordic Semiconductor's nRF52 boards. Starting with a very little amount of theory, you’ll develop code right from the beginning. After you’ve completed this book, you’ll know enough to create your own BLE applications.

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