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The Unitree G1 is a modern humanoid robot that impresses with its remarkable flexibility and advanced technology. With an exceptionally wide range of joint movement and up to 43 joint motors, it exceeds the agility of a typical human. Powered by imitation learning and reinforcement learning, its robotic systems are continuously developed and optimized through artificial intelligence. One of the G1's most impressive features is its ability to autonomously move into a walking position as soon as it touches the ground – no external assistance required! It can immediately start moving, demonstrating a high level of independence and adaptability. The G1 is also equipped with a force-controlled, highly dexterous hand that operates with both sensitivity and precision, thanks to its combination of force and position control. This hand closely mimics human movements, allowing for precise object manipulation. Features Intel RealSense D435 Depth Camera Livox MID-360 3D LiDAR Microphone array (noise and echo cancellation) 5 W stereo speaker Extra large quick release battery Single arm degrees of freedom (shoulder 2 + elbow 2) Hollow joint wiring of the whole machine (no external cables) Maximum torque at joints 120 N.m Single leg degrees of freedom (hip 3, knee 1, ankle 2) Moving speed of 2 m/s Specifications Height, Width and Thickness (Stand) 1320 x 450 x 200 mm Height, Width and Thickness (Fold) 690 x 450 x 300 mm Weight (with Battery) approx. 35 kg Total Degrees of Freedom（Joint Freedom 23 Single Leg Degrees of Freedom 6 Waist Degrees of Freedom 1 Single Arm Degrees of Freedom 5 Joint output bearing Industrial grade crossed roller bearings (high precision, high load capacity) Joint motor Low inertia high-speed internal rotor PMSM (Permanent Magnet Synchronous Motor – better response speed and heat dissipation) Maximum Torque of Knee Joint 90 N.m Arm Maximum Load approx. 2 kg Calf + Thigh Length 0.6 m Arm Span approx. 0.45 m Extra Large Joint Movement Space • Waist joint: Z ±155°• Knee joint: 0~165°• Hip joint: P ±154°, R -30~+170°, Y ±158° Full Joint Hollow Electrical Routing Yes Joint Encoder Dual encoder Cooling System Local air cooling Power Supply 13 string Lithium battery Basic Computing Power 8-core high-performance CPU Sensing Sensor Depth Camera + 3D LiDAR Microphones 4 Microphone Array Speaker 5 W stereo speaker Wireless WiFi 6, Bluetooth 5.2 Smart Battery (Quick Release) 9000 mAh Charger 54 V/5 A Manual Controller Yes Battery Life approx. 2 hours Upgraded Intelligent OTA Yes

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World’s Most Popular ROS Platform TurtleBot is the most popular open source robot for education and research. The new generation TurtleBot3 is a small, low cost, fully programmable, ROS based mobile robot. It is intended to be used for education, research, hobby and product prototyping. Affordable Cost TurtleBot was developed to meet the cost-conscious needs of schools, laboratories and companies. TurtleBot3 is the most affordable robot among the SLAM-able mobile robots equipped with a 360° Laser Distance Sensor LDS-01. ROS Standard The TurtleBot brand is managed by Open Robotics, which develops and maintains ROS. Nowadays, ROS has become the go-to platform for all the roboticists around the world. TurtleBot can be integrated with existing ROS-based robot components, but TurtleBot3 can be an affordable platform for whom want to get started learning ROS. Extensibility TurtleBot3 encourages users to customize its mechanical structure with some alternative options: open source embedded board (as a control board), computer and sensors. TurtleBot3 Waffle Pi is a two-wheeled differential drive type platform but it is able to be structurally and mechanically customized in many ways: Cars, Bikes, Trailers and so on. Extend your ideas beyond imagination with various SBC, sensors and motors on a scalable structure. Modular Actuator for Mobile Robot TurtleBot3 is able to get a precise spatial data by using 2 DYNAMIXEL’s in the wheel joints. DYNAMIXEL XM series can be operated by one of 6 operating modes (XL series: 4 operating modes): Velocity control mode for wheels, Torque control mode or Position control mode for joint, etc. DYNAMIXEL can be used even to make a mobile manipulator which is light but can be precisely controlled with velocity, torque and position control. DYNAMIXEL is a core component that makes TurtleBot3 perfect. It is easy to assemble, maintain, replace and reconfigure. Open Control Board for ROS The control board is open-sourced in hardware wise and in software wise for ROS communication. The open source control board OpenCR1.0 is powerful enough to control not only DYNAMIXEL’s but also ROBOTIS sensors that are frequently being used for basic recognition tasks in cost effective way. Various sensors such as Touch sensor, Infrared sensor, Color sensor and a handful more are available. The OpenCR1.0 has an IMU sensor inside the board so that it can enhance precise control for countless applications. The board has 3.3 V, 5 V, 12 V power supplies to reinforce the available computer device lineups. Open Source The hardware, firmware and software of TurtleBot3 are open source which means that users are welcomed to download, modify and share source codes. All components of TurtleBot3 are manufactured with injection molded plastic to achieve low cost, however, the 3D CAD data is also available for 3D printing. Specifications Maximum translational velocity 0.26 m/s Maximum rotational velocity 1.82 rad/s (104.27 deg/s) Maximum payload 30 kg Size (L x W x H) 281 x 306 x 141 mm Weight (+ SBC + Battery + Sensors) 1.8 kg Threshold of climbing 10 mm or lower Expected operating time 2h Expected charging time 2h 30m SBC (Single Board Computers) Raspberry Pi 4 (2 GB RAM) MCU 32-bit ARM Cortex-M7 with FPU (216 MHz, 462 DMIPS) Remote Controller RC-100B + BT-410 Set (Bluetooth 4, BLE) Actuator XL430-W210 LDS (Laser Distance Sensor) 360 Laser Distance Sensor LDS-01 or LDS-02 Camera Raspberry Pi Camera Module v2.1 IMU Gyroscope 3 AxisAccelerometer 3 Axis Power connectors 3.3 V/800 mA5 V/4 A12 V/1 A Expansion pins GPIO 18 pinsArduino 32 pin Peripheral 3x UART, 1x CAN, 1x SPI, 1x I²C, 5x ADC, 4x 5-pin OLLO DYNAMIXEL ports 3x RS485, 3x TTL Audio Several programmable beep sequences Programmable LEDs 4x User LED Status LEDs 1x Board status LED1x Arduino LED1x Power LED Buttons and Switches 2x Push buttons, 1x Reset button, 2x Dip switch Battery Lithium polymer 11.1 V 1800 mAh / 19.98 Wh 5C PC connection USB Firmware upgrade via USB / via JTAG Power adapter (SMPS) Input: 100-240 VAC 50/60 Hz, 1.5 A @maxOutput: 12 VDC, 5 A Downloads ROS Robot Programming GitHub E-Manual Community

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Elektor GREEN en GOLD leden kunnen deze uitgave hier downloaden. Nog geen lid? Klik hier om een lidmaatschap af te sluiten. Wat is Edge-AI nu eigenlijk?Intelligentie naar het apparaat brengen Maak kennis met Edge Impulse StudioEenvoudig Edge-AI modellen bouwen en implementeren Keyword spotting met Edge ImpulseVerzamelen, trainen en implementeren Slimme apparaten bedienen via spraakbesturing met de Nordic Thingy:53 Sleutelbegrippen voor het begrijpen van Edge AI en Machine Learning Snelcursus: Aan de slag met Edge ImpulseLeer een ML-model te verzamelen, trainen en implementeren met de Arduino Nano 33 BLE Sense Een nieuw hoofdstuk voor ArduinoVan hobbyboard tot Edge computing-krachtpatser Aan de slag met objectdetectie op edge-apparaten Detectie van defecten op printplatenComputer Vision met de Raspberry Pi AI op maat maken voor de kleinste apparaten Optimalisatie van het energieverbruik in batterijgevoede Edge-AI apparaten AI ToasterWanneer Edge-AI en ontbijt samenkomen Thundercomm Rubik Pi 3Raspberry Pi ervaring in combinatie met Edge AI Leiderschap, Embedded ML en de Edge-revolutie Vision language models voor EdgeModel-cascadering voor betere betrouwbaarheid Maak kennis met Edge ImpulseVragen van de Elektor-community Projectupdate #5: Energiemeter op basis van ESP32Edge-AI gebruiken voor herkenning van huishoudelijke verbruikers Bewegingsherkenning met anomalie-detectieEen uitgebreide training Slim ventilatiesysteem: integratie van geluids- en omgevingsgegevensEen machine learning toepassing met dubbele MCU voor geautomatiseerde bediening van ramen en lamellen Spraakbesturing voor oordopjes en headsets Edge-AI: de volgende generatie apparaten mogelijk maken

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Le téléchargement intégral de ce numéro est disponible pour nos membres GOLD et GREEN sur le site Elektor Magazine ! Pas encore membre ? Cliquez ici. qu’est-ce que l’edge AI ?L’IA, intégrée à l’appareil découvrez Edge Impulse StudioConcevez et déployez facilement des modèles d’IA en périphérie détection de mots-clés avec Edge ImpulseCollecter, entraîner et déployer contrôle d’appareils par commande vocale avec le Nordic Thingy:53 Termes clés pour comprendre l’edge AI et le machine learning cours accéléré : démarrez avec Edge ImpulseApprenez à collecter, entraîner et déployer un modèle ML avec l’Arduino Nano 33 BLE Sense un nouveau chapitre pour ArduinoD’une carte pour amateurs à une plateforme d’edge computing premiers pas avec la détection d’objets sur des appareils edge détection de défauts sur circuits imprimésVision par ordinateur avec Raspberry Pi adapter l’IA aux appareils les plus compacts optimiser l’efficacité énergétique des appareils edge AI alimentés sur batterie grille-pain intelligentL’IA qui reconnaît le toast parfait Thundercomm Rubik Pi 3Raspberry Pi et l’edge AI, enfin réunis Leadership, ML embarqué et révolution de l’IA en périphérie modèles vision-langage en périphérieCascade de modèles pour une meilleure fiabilité découvrez Edge ImpulseQuestions de la communauté Elektor mise à jour du projet n°5 : Compteur d’énergie ESP32Utiliser l’Edge AI pour identifier les charges domestiques reconnaissance de mouvements avec détection d’anomaliesUn tutoriel détaillé système de ventilation intelligent : fusion des données sonores et environnementalesUtilisation d’un microcontrôleur double-cœur et du ML pour l’automatisation des fenêtres et persiennes intégrer la commande vocale aux écouteurs et aux casques l'IA en périphérie : au cœur des appareils de demain

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Oscilloscope, multimeter and waveform generator in the same battery-powered device, to work on the go. Features Oscilloscope + multimeter + waveform generator, multifunction in one 3.5-inch high-resolution, high-contrast colour LCD display, suitable for outdoor use 18650 lithium battery, comprehensive power consumption ≤3 W, can work continuously for about 6 hours USB-C interface, support power bank, support PC software connection Self-calibration function SCPI supported, facilitate secondary development Specifications Oscilloscope Bandwidth 70 MHz Channels 2-ch Oscilloscope + 1-ch Generator Sample Rate 250 MSa/s Acquisition Model Normal, Peak detect Record Length 8K Display 3.5-inch LCD Waveform Refresh Rate 10,000 wfrms/s Input Coupling DC, AC, and Ground Input Impedance 1 MΩ ±2%, in parallel with 16pF±10pF Probe Attenuation Factors 1X,10X,100X,1000X,10000X Max. input Voltage 400 V (DC+AC, PK-PK, 1MΩ input impedance) (10:1 probe attenuation) Bandwidth Limit (typical) 20 MHz Horizontal Scale 5 ns/div - 1000 s/div, step by 1 - 2 - 5 Vertical Sensitivity 10 mV/div - 10 V/div Vertical Resolution 8 bits Trigger Type Edge Trigger Modes Auto, Normal, single Automatic Measurement Period, Frequency, Mean, PK-PK, Max, Min Cursor Measurement ΔV, ΔT, ΔT& ΔV between cursors Communication Interface USB Type-C Multimeter Max. Resolution 20,000 counts Testing Mode Voltage, Current, Resistance, Capacitance, Diode, and Continuity test Input Impedance 10 MΩ Max Input Voltage AC: 750 V | DC: 1000 V Max Input Current DC: 10 A | AC: 10 A Diode 0-2 V Waveform Generator Frequency Output Sine 0.1 Hz - 25 MHz Square 0.1 Hz - 5 MHz Ramp 0.1 Hz - 1 MHz Pulse 0.1 Hz - 5 MHz Arbitrary 0.1 Hz - 5 MHz Sampling Rate 125 MSa/s Channel 1-ch Amplitude Range 20 mVpp - 5 Vpp Waveform Length 8K Vertical Resolution 14 bits Output Impedance 50Ω Downloads User Manual for HDS200 Series SCPI Protocol for HDS200 Series Quick Guide for HDS200 Series PC Software for OWON HDS200 Series

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VOYAGE DANS LES RÉSEAUX NEURONAUX (1ÈRE PARTIE)Les neurones artificiels TEST DE PRÉCONFORMITÉ CEM POUR UN PROJET ALIMENTÉ EN COURANT CONTINUPartie 1 : RSIL double continu CHARGE ÉLECTRONIQUE EN CC ET CAJusqu?à 400 V et 10 A (crête) DÉMARRER EN ÉLECTRONIQUE (9)N'ayez pas peur du choc... un peu de « self control » suffit ! TRAITEMENT D'IMAGES AVEC LE MODULE JETSON NANO DE NVIDIA (1ÈRE PARTIE)Matériel et logiciel ZOOM SUR LES TRANSFORMATEURS SECTEURComportement transitoire à l?allumage et l?extinction « YES WE CAN » AVEC PICAN 3Module de bus CAN pour le Raspberry Pi 4 CENTRALE SOLAIRE SUR BALCONUn investissement vite amorti PRISE DE VUE ET DIFFUSION VIDÉO EN CONTINU AVEC UN RASPBERRY PI 4La caméra Raspberry Pi HQ en action UTILISATION D?ÉCRANS DANS LES PROJETS RASPBERRY PIExtrait : écrans à diodes électroluminescentes organiques (OLED) PROPELLER 2 DE PARALLAX (4)Envoi de chaînes de caractères 60 ANS D?ELEKTORRegard sur septembre DANS L?ANTRE DE?Menno van der Veen et de ses tubes amplificateurs CIRCUITS HYBRIDES ROSE DES VENTS AVEC LE CAPTEUR GY-271Ou pourquoi il faut faire des huit pour calibrer un capteur MESUREZ VOTRE EMPREINTEÉlectronique et émissions de gaz à effet de serre THERMOSTAT CONNECTÉ À ESP32Conservez votre vin à la bonne température ! LÉVITATION MAGNÉTIQUE, VERSION NUMÉRIQUEComparateur analogique remplacé par un ESP32 Pico ULTIMATE ARDUINO UNO HARDWARE MANUAL - FR TRANSLATIONExtrait : chargeur d?amorçage du microcontrôleur principal MICROPYTHON POUR L'ESP32 ET SES COPAINSPartie 2 : piloter facilement les écrans matriciels CARTE MADMACHINE SWIFTIOUn langage récent pour du matériel tout nouveau SUR LE VIFPassions incertaines HEXADOKUCasse-tête pour elektorniciens

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Una ricca selezione di articoli dal Mondo Elektor! Gli articoli di questo libro sono una selezione accurata, il "meglio del meglio" di circuiti e progetti recenti, realizzati da tecnici di grande talento provenienti da tutto il mondo. Nel tipico stile di Elektor, questa raccolta offre qualcosa di interessante per tutti, dai progettisti esperti a coloro che praticano l'elettronica nel tempo libero. Sommario Super Servo TesterProva Fino a Quattro Servocomandi, Stand-Alone o in Sistema The TubeUn Insolito Amplificatore a Valvole Cloc 2.0La Sveglia che Avete Sempre Desiderato Stazione Meteo LoRa Low-PowerCostruitevi una Stazione Meteorologica “Long Range” Uscita Video con Microcontrollori (Parte 1)Video Composito Uscita Video con Microcontrollori (Parte 2)Uscita VGA e DVI Un Raspberry Pi Pico come Analizzatore di SpettroFFT su Base Hardware a Basso Costo PIC O’Clock – In Contatto col TempoProgettare un Ricevitore di Segnali Orari SDR Frequenzimetro di Rete ACMisura Frequenza e Tensione della Rete Elettrica Generatore di Funzioni con Arduino NanoNano + Codice = Generatore di Funzioni Monitor CO2Un Approccio Fai-Da-Te per Il Controllo della Qualità dell‘Aria ChatMagLevLa Levitazione Magnetica con AI Alimentatore Lineare Variabile Combinato0…50 V / 0…2 A con Struttura Simmetrica Duale Ricevitore Digitale FM con Arduino e TEA5767Restate in Ascolto con un Arduino Nano Protezione Antigelo per Piante da FruttoCon Registrazione della Temperatura Carico Elettronico con Generatore di clock IntegratoPer Collaudare Alimentatori, Convertitori di Tensione e Batterie 128 Termostato Web con ESP32Mantieni il Vino alla Giusta Temperatura Iniezione di Segnali e di Potenza......per Rilevare le Interruzioni nei Cavi DIY LiPo Supercharger KitDal Prototipo al Mercato di Massa Livella Digitale con Stroboscopio AttivoCalibra il Tuo giradischi con Questo Strumento "Tutto-in-Uno" The Game of Life – 262.144 Modi di GiocareDal Progetto di un Lettore Rilevatore di PerditeCollegato ad Arduino Cloud Orologio di LissajousL’Incedere del Tempo con le Figure di Lissajous Mastermind – Controllato da ArduinoUna Versione Moderna del Classico Gioco di Decifrazione Generatore Audio Analogico 1 kHzOnda Sinusoidale a Bassa Distorsione Aggiorna il tuo Caricabatteria (Parte 1)Non Buttarlo, Modificalo! Aggiorna il tuo Caricabatteria (Parte 2)Non Buttarlo, Modificalo! Sistemi GNSS RTK a Basso CostoCon Accuratezza a Livello Centimetrico Esperimenti a 10 GHz con LNB Satellitari ModificatiSbloccare la Banda X a Basso Costo Telecamera per FerromodellismoInstalla un Modulo ESP32 CAM a Bordo! Monitor di Tensione con MicrocontrolloreProtezione dalla Scarica Profonda per Batterie e Altro Nodo Sensore AutonomoTrasmissione Dati LoRa con Alimentazione a Batterie Solari Layout e Sicurezza sul PCBConsigli per un Progetto Sicuro e Durevole

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UNDERSTANDING THE NEURONS IN NEURAL NETWORKS (PART 1)Artificial Neurons EMC PRE-COMPLIANCE TEST FOR YOUR DC-POWERED PROJECT (PART 1)Dual DC LISN ELECTRONIC LOAD FOR DC AND ACUp to 400 V and 10 A (Peak) STARTING OUT IN ELECTRONICSEasier Than Imagined! ...Taking on the Choke! IMAGE PROCESSING WITH THE NVIDIA JETSON NANO (PART 1)The Hardware and Software AN IN-DEPTH LOOK AT MAINS TRANSFORMERSHow Do They Behave When They Are Switched On and Off? YES WE CAN WITH PICAN 3A CAN Bus HAT for the Raspberry Pi 4 BALCONY POWER PLANTDIY Solar Balcony = Speedy Payback! IMAGING AND VIDEO-STREAMING WITH A RASPBERRY PI 4The Raspberry Pi High-Quality Camera in Practice USING DISPLAYS IN RASPBERRY PI PROJECTSSample Chapter: Organic Light Emitting Diode Displays (OLED) HANDS ON THE PARALLAX PROPELLER 2 (PART 4)Sending Strings ELEKTOR @ 60A Look Back at Previous Septembers HOMELAB TOURSIn the Friesian Countryside, Where the Tubes Bloom ... HYBRIDSPeculiar Parts, the series A COMPASS ROSE USING THE GY-271Or Why We Move in Figures of Eight to Calibrate a Sensor FINDING YOUR FOOTPRINTCalculate the Carbon Footprint of Your Electronics ESP32-CONNECTED THERMOSTATKeep Your Wine at the Right Temperature! MAGNETIC LEVITATION THE DIGITAL WAYESP32 Pico Replaces the Analog Comparator ULTIMATE ARDUINO UNO HARDWARE MANUALSample Chapter: Main Microcontroller Bootloader MICROPYTHON FOR THE ESP32 AND FRIENDS (PART 2)Control Matrix Displays Easily MADMACHINE SWIFTIO BOARDModern Language Meets Modern Hardware FROM LIFE’S EXPERIENCEOn-Again, Off-Again Relationship HEXADOKUThe Original Elektorized Sudoku

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Diese Ausgabe steht allen GOLD- und GREEN-Mitgliedern auf der ElektorMagazine-Website zum Download bereit! Sie sind noch kein Mitglied? Hier klicken! Was genau ist eigentlich Edge-KI?Intelligenz direkt im Gerät Wir stellen vor: Edge Impulse StudioKI-Modelle für Edge-Geräte einfach erstellen und bereitstellen Keyword Spotting mit Edge ImpulseErfassen, Trainieren und Implementieren Intelligente Gerätesteuerung per Sprachbefehl mit Nordic Thingy:53 Edge-KISchlüsselbegriffe zum Verständnis von Edge-KI und Machine Learning Crashkurs: Einstieg in Edge ImpulseWie Sie mit dem Arduino Nano 33 BLE Sense ein ML-Modell erfassen, trainieren und bereitstellen Ein neues Kapitel für ArduinoVom Hobby-Board zur Edge-Computing-Plattform Erste Schritte mit Objekterkennung auf Edge-Geräten Fehlererkennung auf LeiterplattenComputer Vision mit dem Raspberry Pi KI-Skalierung für kleinste Geräte Optimierung der Energieeffizienz bei batteriebetriebenen Edge-KI-Geräten KI-ToasterWenn Edge-KI das Frühstück rettet Thundercomm Rubik Pi 3Raspberry Pi trifft Edge-KI Unternehmensführung, Embedded ML und die Edge-Revolution Vision-Language-Modelle für Edge-GeräteKaskadierte Modelle für höhere Zuverlässigkeit Lernen Sie Edge Impulse kennenFragen aus der Elektor-Community Projekt-Update #5: Energiemessgerät mit ESP32Haushaltsgeräte mit Edge-KI erkennen Bewegungserkennung mit Anomalie-ErkennungEin End-to-End-Tutorial Intelligentes Belüftungssystem: Verbindung von Schall- und UmweltdatenEin Dual-MCU-Ansatz mit Machine Learning für die automatische Steuerung von Fenstern und Jalousien Sprachsteuerung für Ohrhörer und Headsets Edge-KI: Intelligente Geräte auf dem Vormarsch

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Microcontrollers have become an indispensable part of modern electronics. They make things possible that vastly exceed what could be done previously. Innumerable applications show that almost nothing is impossible. There’s thus every reason to learn more about them, but that raises the question of where to find a good introduction to this fascinating technology. The answer is easy: this Microcontroller Basics book, combined with the 89S8252 Flash Board project published by Elektor Electronics. However, this book offers more than just a basic introduction. It clearly explains the technology using various microcontroller circuits and programs written in several different programming languages. Three microcontrollers from the 8051 family are used in the sample applications, ranging from the simple 89C2051 to the AN2131, which is designed to support USB applications. The programming tools include assemblers, Basic-52 and BASCOM-51, and several C compilers. Every reader can thus find the programming environment most suitable to his or her needs. In the course of the book, the reader gradually develops increased competence in converting his or her ideas into microcontroller circuitry. All of the sample programs can be downloaded from the Elektor Electronics website or the author’s website. That has the added advantage that the latest versions are always available.

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Dieses Buch ist eine Einführung in das hochaktuelle Gebiet der Robotik. Dabei stehen praktische Anwendungsbeispiele im Vordergrund. Neben den technischen und mechanischen Grundlagen werden die elektronischen Komponenten und Module erläutert. Eine zentrale Rolle spielt dabei der Mikrocontroller. Für Robotik-Anwendungen haben sich zwei Controller-Boards etabliert: der Arduino und der Raspberry Pi. Dem trägt dieses Buch Rechnung und beschreibt praktische Nachbauprojekte mit diesen beiden populären Boards. Getreu der Philosophie des „Learning by Doing“ können sich auch ambitionierte, nichtprofessionelle Anwender mit dem Lernmaterial des Buches einen Überblick über den neuesten Stand der Robotertechnik und KI verschaffen. Für praktische Anwendungen können sowohl komplette Bausätze als auch einzelne Komponenten verwendet werden. Dabei wurde stets darauf geachtet, dass die Hardware möglichst universell einsetzbar ist.

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Dieses Buch ist eine Einführung in das hochaktuelle Gebiet der Robotik. Dabei stehen praktische Anwendungsbeispiele im Vordergrund. Neben den technischen und mechanischen Grundlagen werden die elektronischen Komponenten und Module erläutert. Eine zentrale Rolle spielt dabei der Mikrocontroller. Für Robotik-Anwendungen haben sich zwei Controller-Boards etabliert: der Arduino und der Raspberry Pi. Dem trägt dieses Buch Rechnung und beschreibt praktische Nachbauprojekte mit diesen beiden populären Boards. Getreu der Philosophie des „Learning by Doing“ können sich auch ambitionierte, nichtprofessionelle Anwender mit dem Lernmaterial des Buches einen Überblick über den neuesten Stand der Robotertechnik und KI verschaffen. Für praktische Anwendungen können sowohl komplette Bausätze als auch einzelne Komponenten verwendet werden. Dabei wurde stets darauf geachtet, dass die Hardware möglichst universell einsetzbar ist.

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