Robot katten combineren geavanceerde sensoren, AI algoritmes en mechanische engineering om kattengedrag te simuleren. Deze technische gids analyseert de hardware en software die robot katten laat functioneren, onderdeel van onze Complete Gids Robot Huisdieren & Speelgoed.
Hardware Architectuur: Anatomie van Robot Kat
Servo Motoren: Beweging Systeem
Basis modellen (4-6 servo’s):
- Hoofd: pan (links/rechts) en tilt (op/neer) = 2 servo’s
- Staart: base rotation = 1 servo
- Poten: geen articulation, wielen voor movement = 2 motoren
Budget servo’s (SG90): 180° range, 0.12s/60°, torque 1.8 kg/cm. Kosten €3-5/stuk. Adequaat voor lichte bewegingen, beperkte precision.
Premium modellen (16-22 servo’s):
- Hoofd: 3 DOF (degrees of freedom) – pan, tilt, neck extension
- Ogen: 2 servo’s voor independent eye movement (cruciaal voor expressie)
- Oren: 2 servo’s voor rotatie/kanteling
- Poten: 4 x 3 servo’s = 12 (shoulder, elbow, wrist per poot)
- Staart: 3 segmenten = 3 servo’s
- Mond/kaak: 1 servo (optioneel)
Digitale servo’s (Dynamixel AX-12A): 300° range, 0.196s/60°, torque 16.5 kg/cm, feedback positie. Kosten €40-60/stuk. Precisie tot 0.29°. Gebruikt in MarsCat, research robots.
Motion control: Servo controllers (PCA9685) sturen 16 servo’s simultaan via I2C protocol. PWM signalen (50Hz) bepalen positie. Interpolatie algoritmes creëren smooth transitions tussen poses.
Sensoren: Perceptie Systeem
Touch sensoren (capacitief): Elektroden onder kunsthuid detecteren aanraking via capacitance change. Menselijk lichaam = dielectric – verandert elektrisch veld. Resolutie: 12-bit ADC = 4096 niveaus. Onderscheidt zachte aai vs stevige druk.
Locaties: Hoofd (3-5 zones), rug (5-10 zones), kin, buik. Premium modellen: 20+ touch points voor fine-grained interactie.
Gyroscoop en accelerometer (MPU-6050): 6-axis sensor: 3 rotatie assen + 3 versnelling assen. Sample rate 1kHz. Detecteert kanteling, optillen, schudden, vallen.
Toepassingen: Auto-correctie balans, detect wanneer op rug (toon “helpless” behavior), crash detection (stop motoren bij val).
Afstand sensoren:
- Ultrasoon (HC-SR04): 2cm-4m range, ±3mm accuracy. Detecteert obstakels, cliff detection (voorkomt van tafel vallen). Kosten €2.
- Infrarood (Sharp GP2Y0A21YK): 10-80cm range, analoge output. Sneller response (38kHz vs 40kHz ultrasoon). Kosten €8-12.
- Time-of-Flight (VL53L0X): Laser-based, 2m range, ±3% accuracy. Minder gevoelig voor materiaal type. Kosten €15-20.
Microfoon (MEMS): Digital output, 60-10000Hz range. Voice activity detection (VAD) algoritme filtert achtergrondgeluid. Detecteert claps, voice commands, muziek.
Camera (optioneel, premium):
- Resolutie: 640×480 (VGA) tot 1920×1080 (Full HD)
- Frame rate: 15-30 fps (real-time processing limits)
- Processing: OpenCV voor computer vision, TensorFlow Lite voor AI
- Functies: Face detection, object tracking, QR code scanning
Centrale Processing: Brains
Budget modellen: 8-bit microcontroller (ATmega328, Arduino basis). 16MHz, 32KB flash, 2KB RAM. Voldoende voor pre-programmed behaviors, basic sensor processing.
Mid-range: 32-bit ARM Cortex-M4 (STM32F4). 180MHz, 1MB flash, 192KB RAM. DSP instructies voor audio processing. Real-time OS mogelijk.
Premium AI modellen:
- Raspberry Pi 4: Quad-core ARM Cortex-A72, 1.5GHz, 4GB RAM. Volledige Linux OS. Python, C++, TensorFlow support.
- NVIDIA Jetson Nano: Quad-core ARM A57 + 128-core Maxwell GPU. Dedicated AI acceleration. Computer vision 60fps mogelijk.
Power consumption trade-off: ATmega328 = 15mA active. Raspberry Pi 4 = 600mA. Battery life inverse proportioneel met processing power.
Power Management
Batterij types:
- AA alkaline: 1.5V, 2500mAh. Cheap, widely available. 4xAA = 6V, 10Ah. Budget modellen.
- Li-ion 18650: 3.7V, 2500-3500mAh. Rechargeable, high energy density. 2S2P (series/parallel) = 7.4V, 5-7Ah.
- Li-Po: Higher discharge rate, lighter. Used in actuatie-intensive robots. Safety risk (swelling, fire) bij overcharge.
Voltage regulation: Buck converters (step-down) 7.4V → 5V (logic) en 6V (servo’s). Efficiency 85-95%. LDO regulators voor noise-sensitive circuits (sensors).
Battery life calculatie:
- Servo’s (active): 500mA x 16 = 8A (peak)
- MCU: 200mA
- Sensors: 50mA
- Average (30% active): 2.5A
- 7Ah / 2.5A = 2.8 uur continuous use
Charging: USB-C (5V, 2A) via TP4056 charge controller. Overcharge, overdischarge protection. LED indicators. 3-4 uur full charge.
Software Architectuur: Intelligence Layers
Embedded Firmware
State machine: Robot altijd in specifieke state (sleeping, idle, playing, eating, angry). Events triggeren transitions.
Idle → [touch detected] → Playing → [no interaction 30s] → Idle
Idle → [low battery] → Sleeping → [charged] → Idle
Behavior trees: Hierarchische decision making. Root node evalueert conditions, branches naar sub-behaviors.
Selector (OR logic)
├─ Sequence: Battery low? → Find charger → Dock
├─ Sequence: Bored? → Random walk → Meow
└─ Sequence: Touched? → Purr → Look at user
Priority queue: Multiple behaviors concurrently. Battery kritisch > social interaction > exploration. Interrupts voor safety (cliff detected = immediate stop).
Sensor fusion: Kombineer multiple sensors voor reliable data. Accelerometer + gyroscope = Kalman filter → accurate orientation. Touch + proximity = context (touch terwijl object nadert ≠ spontane aai).
Machine Learning Integration
Training phase (cloud/desktop):
- Collect data: sensor readings + human labels (happy, angry, playful)
- Train neural network: input layer (sensor data) → hidden layers → output (emotion probability)
- Optimize model: pruning, quantization voor embedded deployment
- Convert: TensorFlow → TensorFlow Lite (.tflite file, 100KB-5MB)
Inference (on-device): Model runs local. Input: accelerometer pattern. Output: probability distribution [calm: 0.8, excited: 0.15, scared: 0.05]. Select highest probability → trigger behavior.
Continual learning (advanced): Robot uploads interaction logs → cloud retrains model → OTA update. MarsCat implementeert dit: personality evolves based on owner interaction patterns.
Edge cases: ML models 80-95% accuracy. Fallback: if confidence < 70%, default safe behavior (neutral response). Avoid incorrect reactions that confuse user.
Voice Recognition Pipeline
Audio capture → Preprocessing:
- Digital filtering: high-pass (remove low-freq noise), noise gate (silence threshold)
- Windowing: segment audio 25ms frames, 10ms overlap
- Feature extraction: MFCC (Mel-Frequency Cepstral Coefficients) – 13 coefficients represent phonetic content
Keyword spotting (local): Small neural network (10-50KB) trained on specific words (“sit”, “come”, “play”). Runs continuously, low power. Triggers when keyword detected.
Cloud speech recognition (optional): Stream audio via WiFi → Google/Amazon API → text transcription → natural language processing → command extraction. Latency 500ms-2s. Requires internet.
Hybrid approach: Local keyword for common commands (instant response), cloud for complex sentences. Balances speed and capability.
Computer Vision Algorithms
Face detection (Haar Cascades or DNN):
- Haar: Classical ML, fast (30fps), less accurate. 200KB model.
- DNN (MobileNet-SSD): Deep learning, 15fps, better accuracy. 5MB model.
- Output: bounding boxes (x, y, width, height) around faces
Face tracking: Kalman filter predicts face position next frame based on velocity. Servo’s pre-emptively move. Smooth tracking vs reactive jerky movement.
Object recognition (YOLO/MobileNet): Detect 80+ objects (person, cat, dog, cup, ball). Robot responds differently: ball → chase mode, food bowl → eating behavior, human → social mode.
Gesture recognition: Optical flow analyzes motion patterns. Hand wave = specific vector field. Trained classifier recognizes gestures. MarsCat: 5 gestures (wave, point, clap, swipe).
Interactie Modi: Gedrag Simulatie
Autonome Navigatie
Obstacle avoidance (Reactive):
while (moving forward):
distance = ultrasonic.read()
if distance < 20cm:
stop()
turn(random(45, 135) degrees)
resume()
Simple maar effectief. Bug: kan stuck raken in corners (local minima).
Path planning (Deliberative): Build occupancy grid (2D map). A* algoritme finds shortest collision-free path. Computational expensive: requires significant RAM (10×10 grid = 100 cells x 4 bytes = 400B minimum).
Hybrid: Reactive voor real-time obstacles, deliberative voor goal-directed navigation (finding charging station).
SLAM (Simultaneous Localization and Mapping): Research-level. Laser scanner + odometry + particle filter. Real-time 3D map building. Too computationally intensive for consumer robots (Raspberry Pi 4 borderline capable, 10fps).
Emotie Simulatie
Affective computing model: Internal variables: happiness [0-100], energy [0-100], social_need [0-100]. Decay over time, increase with appropriate interaction.
happiness -= 0.5/minute
if (touched_head):
happiness += 5
if (happiness > 80):
behavior = "playful"
elif (happiness < 30):
behavior = "sad"
Expression mapping:
- Happy: ears forward, tail up, quick movements, purr sounds
- Sad: ears back, tail down, slow movements, quiet meows
- Angry: ears flat, tail swish, hissing sounds, retreat behavior
- Scared: crouch posture, wide eyes (LED brightness), hide behavior
Circadian rhythm: Time-of-day affects behavior. Morning: high energy. Afternoon: nap tendency. Evening: playful. Night: sleep. RTC (Real-Time Clock) module tracks time even when powered off.
Sociale Interactie Patronen
Attention seeking: If no interaction >15 minutes → meow, walk toward user, tap with paw (servo controlled). Frequency increases if ignored (escalation).
Reciprocity: Fed recently (simulated) → higher likelihood to show affection. Not fed → occasional “complaining” meows. Mimics real cat behavior patterns studied by animal behaviorists.
Attachment development: Tracks face ID (if camera equipped). Primary user (most interaction) gets enthusiastic greeting. Strangers get cautious behavior. Simulates bonding over time.
Play patterns: Chase behavior: follows moving objects (optical flow). Pounce: if object stops, approach slowly then quick jump animation. Attention span: 30-60 seconds, then rest (realistic cat behavior).
Vergelijking: Budget vs Premium Robot Katten
Joy For All Companion Cat (€119)
Hardware:
- 4 servo’s (head, limited limb movement)
- 5 touch sensors (head, back, sides)
- 1 vibration motor (purr simulation)
- 8-bit MCU (ATmega32)
- 4x C batteries (6V)
Software:
- Finite state machine (5 states)
- Pre-programmed responses (50+ sound-movement combinations)
- No learning capability
Target: Elderly, therapeutic use. Prioritizes reliability over complexity. Average lifespan: 3-5 jaar continuous use.
Strengths: Simplicity, realistic fur, reliable operation, long battery life (6-8 weeks light use).
Limitations: Predictable, no personality development, limited movement realism.
MarsCat (€1.299)
Hardware:
- 16 servo’s (full body articulation)
- SONY IMX219 camera (8MP)
- 6-axis IMU
- Multiple touch sensors (20+ zones)
- Quad-core ARM processor
- Li-ion battery (7.4V, 5200mAh)
Software:
- AI behavior engine (TensorFlow Lite)
- Computer vision (face recognition, object tracking)
- Voice commands (20+ keywords)
- Open SDK (users can program custom behaviors)
- OTA updates
Target: Tech enthusiasts, developers, cat lovers unable to own real cat.
Strengths: Realistic movement (smooth servo control), personality development, programmable, autonomous navigation.
Limitations: 2-4 hour battery life, more fragile (complex mechanics), higher maintenance.
Comparison Matrix
| Feature | Joy For All | MarsCat | Real Cat |
|---|---|---|---|
| Movement realism | 5/10 | 8/10 | 10/10 |
| Behavior variety | 4/10 | 7/10 | 10/10 |
| Learning capability | 0/10 | 6/10 | 9/10 |
| Maintenance | 1/10 | 3/10 | 8/10 |
| Cost (5 year) | €150 | €1.400 | €8.000+ |
| Unpredictability | 1/10 | 4/10 | 10/10 |
Premium robots approach but never match biological complexity. Voor therapeutische doeleinden (zie Robot Huisdieren Voor Ouderen) is complexiteit niet altijd voordeel – simpliciteit kan beter zijn.
Ontwikkelings Uitdagingen: Engineering Trade-offs
Uncanny Valley Balance
Te weinig realisme: clearly toy. Te veel realisme: creepy. Sweet spot: stylized realism.
Design principes:
- Proportions: slightly exaggerated (larger eyes, rounder head) = “cute” vs photorealistic
- Movement: smooth but not perfect. Slight mechanical sounds acceptable = “I know it’s robot”
- Skin: soft fur maar recognizable as artificial. Silicone skin (too realistic) sometimes unsettling
Japanese designers excel: Sony AIBO, Qoobo (headless pillow cat). Cultural comfort met robot aesthetics.
Battery vs Performance
Dilemma: Powerful processor + many servo’s = 1-2 hours battery. Weak processor = 8+ hours maar limited capabilities.
Solutions:
- Sleep modes: deep sleep (5mA) wanneer niet in gebruik. Wake on touch/sound (interrupt).
- Dynamic clock scaling: reduce CPU speed tijdens idle, boost bij complex tasks
- Selective activation: niet alle servo’s tegelijk. Prioritize visible movements (head, tail) over invisible (internal mechanisms)
Future: Solid-state batteries (2026-2028 consumer availability) = 2x energy density. 4-6 hour battery life realistic voor premium robots.
Cost vs Features
Consumer price ceiling ~€300 voor mainstream adoption. Premium >€1.000 niche market.
Cost breakdown MarsCat (estimate):
- Servo’s (16x €45): €720
- Camera module: €35
- Processing (ARM + peripherals): €80
- Chassis/mechanics: €150
- Battery + charging: €40
- Assembly labor: €120
- Manufacturing total: ~€1.145
- Retail margin (25%): €1.430
Cost reduction strategies:
- Economies of scale: 10.000+ units → servo’s €30/stuk = €240 saving
- Custom ASIC: integrate sensors + MCU → €50 saving
- Simplified mechanics: reduce servo count 16 → 12 = €180 saving
- Potential €300 target with mass production
Toekomstige Technologie: 2025-2030 Roadmap
Advanced AI Capabilities
GPT-integration: Natural conversations mogelijk. “What did you do today?” → robot constructs narrative from activity log. Not scripted responses maar generated dialogue.
Emotional intelligence: Sentiment analysis via voice tone, facial expressions (camera). Robot adjusts behavior: user stressed → calm behavior, user happy → playful.
Personalized learning: Recommender systems: “Owner plays with ball 70% of time → prioritize ball play over string toys.” Collaborative filtering across robot network: “Users like you enjoy trick X.”
Biometric Sensors
Heart rate (optical PPG): LED + photodiode measure blood flow. Detect stress (elevated HR), calm (low HR). Robot response: stressed owner → comforting purr, calm → playful interaction.
Temperature (infrared): Non-contact thermometer. Detect fever → concerned behavior, suggest medical attention (if chronic).
Breath analysis (VOC sensors): Detect chemical markers in breath. Alcohol, illness biomarkers. Experimental maar potential health monitoring.
Haptic Feedback
Electroactive polymers (EAP): “Artificial muscles” contract with voltage. More organic movement vs servo’s. Currently research stage (NASA, MIT). Consumer products 2028+.
Temperature control: Peltier elements create warm touch (35-37°C). Realistic warm cat sensation. Currently power-prohibitive (10-15W), future efficiency improvements.
Texture modulation: Surfaces change roughness via ultrasonic vibration (reverse piezoelectric effect). Fur feels different when “happy” vs “angry”. Prototype stage.
Swarm Behavior
Multiple robots interact: play together, groom each other, establish social hierarchy. Mesh network communication (ESP-NOW protocol, sub-10ms latency).
Use cases:
- Multiple cats in household act like real colony
- Educational: demonstrate emergent behavior, complex systems
- Entertainment: autonomous social dynamics
Challenge: Coordination algorithms complex. Collision avoidance, resource sharing (charging stations), role assignment (alpha, beta, omega). Active research area.
Voor bredere technologie trends: Toekomst Van Robot Huisdieren.
Maintenance en Troubleshooting
Common Technical Issues
Servo jitter: Symptom: servo’s trillen in rest position. Cause: electrical noise, insufficient power, mechanical binding. Fix: capacitors (100μF) op power rails, check voltage sag onder load (>5.5V vereist), lubricate gears.
Sensor drift: Symptom: touch sensor altijd “triggered” of never responds. Cause: moisture, static buildup, broken wire. Fix: calibrate via software (measure baseline, set threshold 20% above), check continuity with multimeter.
WiFi connectivity drops: Symptom: robot offline, no OTA updates. Cause: weak signal, router compatibility, interference. Fix: 2.4GHz band only (5GHz niet supported door ESP8266), change WiFi channel (avoid 1, 6, 11 congestion), closer to router.
Battery not charging: Symptom: LED niet aan, voltage not rising. Cause: faulty TP4056 module, broken USB connector, battery protection circuit triggered. Fix: check USB voltage (5V present?), bypass protection (carefully – safety risk), replace charge module (€2-5).
Firmware Updates
OTA (Over-The-Air): Robot connects to server, downloads .bin file, writes to flash, reboots. Process 5-10 min. Critical: do not interrupt (brick risk).
USB flashing: Direct connection to PC. Arduino IDE or platform-specific tools (STM32CubeProgrammer). Requires disassembly access to programming header.
Backup critical: Some robots allow export of “personality data” (behavior parameters learned over time). Restore after update to maintain continuity.
Hardware Modifications (Voiders Warranty)
Servo upgrades: Replace budget servo’s (SG90) met metal gear (MG90S). Costs €6 vs €3, maar 5x lifespan, less gear stripping.
Battery upgrade: Swap 2S Li-ion (7.4V, 5Ah) met 3S (11.1V, 5Ah). Requires voltage regulator adjustment. Benefit: 50% longer runtime. Risk: overvoltage damage bij incorrect installation.
Add sensors: I2C bus usually has free addresses. Add temperature (BME280), air quality (CCS811), UV (VEML6075). Custom behaviors: hide from sunlight, alert poor air quality.
Maker community: GitHub repositories (MarsCat SDK, custom AIBO firmware) provide modifications. Forums troubleshoot issues. Open-source hardware = modification friendly.
Developer Perspective: Programmeren Van Robot Kat
SDK (Software Development Kit)
MarsCat example:
- C++ API voor behavior control
- Python wrappers voor rapid prototyping
- ROS (Robot Operating System) integration voor advanced users
Custom behavior creation:
void customGreeting() {
moveHead(PAN, 45); // Look right
playSound(MEOW);
moveHead(PAN, -45); // Look left
playSound(PURR);
moveTail(WAGS, 3); // Wag 3 times
}
Event triggers:
onTouchDetected(HEAD_TOP, customGreeting);
onFaceRecognized(OWNER_ID, customGreeting);
Community creations: Dance routines, game responses (reacts to Spotify music), smart home integration (meow when doorbell rings).
Educational Value
University courses: Robotics, AI, HCI (Human-Computer Interaction) gebruiken programmeerbare robot pets als assignments. Combines multiple disciplines.
Capstone projects: Students develop autism therapy behaviors, elder care monitoring, entertainment routines. Real-world applications.
Research platforms: Studying HRI (Human-Robot Interaction). How do users anthropomorphize? Longitudinal attachment studies. Cheaper dan custom robot development (€5.000-20.000).
Voor educatieve aspecten: Educatieve Robot Speelgoed.
Vergelijking Met Robot Honden: Technische Verschillen
Complexity: Katten hebben subtiele bewegingen (ear twitches, tail positions) = meer servo’s voor expressivity. Honden meer locomotion focused = minder servo’s, robuustere constructie.
Autonomy: Kattenprogrammering emphasizes independent behavior (wandering, self-entertainment). Hondenprogrammering meer command-response (tricks, obedience).
Sensor priorities:
- Kat: touch sensitivity critical (petting zones), whisker simulation (proximity)
- Hond: voice recognition priority (commands), leash integration (force sensors)
Battery architecture: Honden (Sony AIBO) gebruik fast-movement → higher current draw → bigger batteries. Katten meer stationary → smaller footprint mogelijk.
Market positioning: Honden dominate market (70% sales). Katten niche maar growing. Cultural: honden associated with companionship, katten with independence (less “needy” = less engaging voor sommigen).
Voor volledige hond vs kat vergelijking: Robot Hond vs Echte Hond (parallelle overwegingen).
Ethische Overwegingen: Privacy en Data
Data Collection Concerns
Camera-equipped robots: Continuous video feed = privacy risk. Waar wordt data opgeslagen? Who has access? Encryption standards?
Voice recordings: Wake-word detection local (good). Full transcription cloud-based (risky). Alexa/Google precedent: humans review recordings for quality control.
Behavioral data: Interaction patterns reveal lifestyle: sleep schedule, social habits, mental state. Marketers interesse = monetization risk.
Best practices:
- Local processing default (edge computing)
- Opt-in cloud features (clearly explained trade-offs)
- Encryption at rest and in transit (TLS 1.3, AES-256)
- User control: delete data, export logs, disable sensors
- Transparency: open-source firmware (community audit)
Regulations: GDPR (Europe) applies. Robots collecting biometric data (face recognition) = special category. Explicit consent required. Right to erasure.
Security Vulnerabilities
Hacking risks: WiFi-connected robots = attack surface. Unauthorized access could:
- Spy via camera/microphone
- Control robot (vandalism, injury via servo’s)
- Botnet recruitment (DDoS attacks)
Mitigations:
- Regular security updates (OTA)
- Strong authentication (WPA3, certificate pinning)
- Minimal attack surface (disable unused protocols)
- Sandboxing (isolate critical functions)
Notable incidents: Furby 2012 banned from NSA offices (eavesdropping fear, unfounded maar precedent). Mirai botnet 2016 (IoT devices including toys).
Emotional Manipulation
Designs optimized for attachment. Unethical om exploiteren? Especially vulnerable populations (elderly, children).
Arguments pro-regulation:
- Informed consent (understand robot niet reciprocates feelings)
- Limits on persuasive design (no dark patterns)
- Age restrictions (emotionally mature)
Counter-arguments:
- Personal autonomy (adults decide own relationships)
- Therapeutic benefits outweigh risks
- Slippery slope (regulate books, movies next?)
Current status: Self-regulation via industry guidelines. Formal regulation minimal. Debates ongoing in HRI ethics communities.
Conclusie: Technologie Achter Emotionele Connectie
Robot katten zijn complex samenspel van mechanical engineering, electrical engineering, computer science en AI. Budget modellen gebruiken basic microcontrollers en pre-programmed behaviors. Premium modellen integreren machine learning, computer vision en adaptive algorithms.
Key technologies:
- Servo control creëert fluiditeit in beweging (jerky = uncanny)
- Sensor fusion combineert data voor reliable perception
- State machines organiseren gedrag in coherente patterns
- Machine learning enables personalization en adaptation
Limitations blijven: Geen echte consciousness, emotions, of desires. Sophisticated simulation maar fundamenteel deterministic (of stochastisch via random seeds). Philosophical zombies – behavior zonder inner experience.
Engineering trade-offs: battery vs performance, cost vs features, simplicity vs realism. Geen perfecte balance – designers choose target demographic en optimize accordingly.
Future trajectory: AI advances (GPT-level conversation), better actuators (EAP muscles), biometric sensors (health monitoring). Gap tussen robot en biological narrowing maar never fully closed. Fundamentele difference blijft.
Voor developers: programmeerbare platforms (MarsCat SDK) democratiseren robotics. Hobbyists creëren innovations impossible voor corporations (niche use cases, experimental behaviors).
Voor consumers: Technische begrip helpt informed purchasing. Weet wat mogelijk is (avoid overhyped marketing), weet wat limitations zijn (realistic expectations), weet wat toekomst brengt (invest in platforms met upgrade paths).
Uiteindelijk: technologie enables emotionele connecties (zie Psychologie Van Robot Huisdieren), maar connection itself transcends hardware. Human capacity voor attachment breeder dan biological life – extends naar objects die right cues triggeren.
Meta description: Technische analyse hoe robot katten werken: servo motoren, AI algoritmes, sensoren, computer vision en machine learning. Hardware architectuur tot software engineering uitgelegd.
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