Robotics
LeRobot
English
Korean
physical-ai
embodied-ai
humanoid
quadruped
hexapod
connectome
neuromorphic
spiking-neural-networks
snn
brain-inspired
drosophila
malecns-2026
sim-to-real
edge-ai
green-ai
arduino
esp32
webgl
threejs
reinforcement-learning
Eval Results (legacy)
Instructions to use hwihwalab/neuro-robo-connectome with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use hwihwalab/neuro-robo-connectome with LeRobot:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- README.md +10 -10
- README_KR.md +6 -6
- neuro_robo_bundle.zip +2 -2
README.md
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training_type: "biological-connectome-extraction"
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geographical_location: "South Korea"
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hardware_used: "ESP32-S3 / Arduino Uno"
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model-index:
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type: robotics
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name: Physical AI Multi-Body Locomotion & Chemotaxis
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dataset:
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name: MaleCNS
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type: connectome/
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metrics:
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value: 100.0
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name: Total Synaptic Connections
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---
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# 🧠
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[](README.md)
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[](README_KR.md)
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[](https://opensource.org/licenses/MIT)
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[](https://huggingface.co/lerobot)
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[](#-5-empirical-benchmark--key-experimental-results)
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[-22c55e?style=for-the-badge)](#-6-computational-efficiency--green-ai-metrics)
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[](#-4-hardware--robot-platform-compatibility-matrix)
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[](./arduino_esp32_firmware.cpp)
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> **166,745-Neuron Whole-Brain Fruit Fly Connectome Foundation Model for Biomorphic Multi-Body Robotics & Sim-to-Real Embedded Control.**
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> *[ 🌐 English Documentation ](README.md) | [ 🇰🇷 한국어 매뉴얼 ](README_KR.md) | [ 🎮 Live Interactive 3D Demo ](https://huggingface.co/spaces/hwihwalab/neuro-robo-studio)*
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| Parameter / Metric | Specification & Empirical Result | Architecture & Domain |
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| :--- | :--- | :--- |
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| **Model Name** | `neuro-robo-connectome` | Physical AI, LeRobot, Connectome Robotics, MaleCNS |
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| **Biological Substrate** | Adult Male *Drosophila
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| **Neural Scale** | **166,745 Neurons · 2
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| **End-to-End Latency** | **5.67 ms** (ORN ➔ ALPN ➔ DN ➔ MN closed-loop) | Ultra-low latency, Real-time 100Hz control |
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| **Power Consumption** | **0.05 W** (MCU execution) vs **700 W** (Cloud GPU VLA) | Green AI, 14,000x energy efficiency, Edge AI |
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| **Supported Robot Bodies** | **8 Biomorphic Bodies** (CyberFly, Go1, G1, T1, MicroDuck, BH, Drone, AGV) | Hexapod, Quadruped, Bipedal Humanoid, Ornithopter, AMR |
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## 📌 1. Model Description (Overview)
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**
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Operating at **under 10ms end-to-end latency (5.67ms empirical)** and requiring **less than 0.05W of power (14,000x lower energy than cloud LLM/VLA models)**, this model drives 8 biomorphic robot bodies across diverse physical terrains for closed-loop chemotaxis pursuit and obstacle avoidance without requiring morphology-specific retraining.
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training_type: "biological-connectome-extraction"
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geographical_location: "South Korea"
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hardware_used: "ESP32-S3 / Arduino Uno"
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pretty_name: "Neuro-Robo Connectome: Whole-Brain Physical AI Foundation Model (MaleCNS & FlyWire)"
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size_categories:
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- 10M<n<100M
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model-index:
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type: robotics
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name: Physical AI Multi-Body Locomotion & Chemotaxis
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dataset:
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name: MaleCNS & FlyWire Connectome Graph
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type: connectome/drosophila-dual
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metrics:
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value: 100.0
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name: Total Synaptic Connections
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---
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# 🧠 Neuro-Robo Connectome | Whole-Brain Physical AI Foundation Model for Biomorphic Robotics
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[](README.md)
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[](README_KR.md)
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[](https://opensource.org/licenses/MIT)
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[](https://huggingface.co/lerobot)
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[%20%26%20FlyWire%20(139.2k)-10b981?style=for-the-badge)](https://janelia.org)
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[](#-5-empirical-benchmark--key-experimental-results)
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[-22c55e?style=for-the-badge)](#-6-computational-efficiency--green-ai-metrics)
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[](#-4-hardware--robot-platform-compatibility-matrix)
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[](./arduino_esp32_firmware.cpp)
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> **166,745-Neuron Whole-Brain Fruit Fly Connectome Foundation Model (MaleCNS & FlyWire FAFB) for Biomorphic Multi-Body Robotics & Sim-to-Real Embedded Control.**
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> *[ 🌐 English Documentation ](README.md) | [ 🇰🇷 한국어 매뉴얼 ](README_KR.md) | [ 🎮 Live Interactive 3D Demo ](https://huggingface.co/spaces/hwihwalab/neuro-robo-studio)*
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> [!TIP]
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| Parameter / Metric | Specification & Empirical Result | Architecture & Domain |
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| :--- | :--- | :--- |
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| **Model Name** | `neuro-robo-connectome` | Physical AI, LeRobot, Connectome Robotics, MaleCNS & FlyWire |
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| **Biological Substrate** | Adult Male (MaleCNS) & Female (FlyWire FAFB) *Drosophila* Whole CNS | Nature 2026 MaleCNS Connectome & Princeton FlyWire |
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| **Neural Scale** | **166,745 (Male) / 139,255 (Female) Neurons · 2.75M~3.28M Synapses · 815 Motor Neurons** | Spiking Neural Network (SNN), LIF Neuron Dynamics |
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| **End-to-End Latency** | **5.67 ms** (ORN ➔ ALPN ➔ DN ➔ MN closed-loop) | Ultra-low latency, Real-time 100Hz control |
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| **Power Consumption** | **0.05 W** (MCU execution) vs **700 W** (Cloud GPU VLA) | Green AI, 14,000x energy efficiency, Edge AI |
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| **Supported Robot Bodies** | **8 Biomorphic Bodies** (CyberFly, Go1, G1, T1, MicroDuck, BH, Drone, AGV) | Hexapod, Quadruped, Bipedal Humanoid, Ornithopter, AMR |
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## 📌 1. Model Description (Overview)
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**Neuro-Robo Connectome Physical AI Foundation Model** is a whole-brain neuromorphic foundation model integrating the world's most advanced adult *Drosophila melanogaster* central nervous systems (**MaleCNS 2026: 166,745 neurons & FlyWire FAFB: 139,255 neurons, 2,753,975~3,280,000 synapses, 815 leg motor neurons**).
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Operating at **under 10ms end-to-end latency (5.67ms empirical)** and requiring **less than 0.05W of power (14,000x lower energy than cloud LLM/VLA models)**, this model drives 8 biomorphic robot bodies across diverse physical terrains for closed-loop chemotaxis pursuit and obstacle avoidance without requiring morphology-specific retraining.
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# 🧠
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[](https://opensource.org/licenses/MIT)
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[](https://huggingface.co/lerobot)
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[](#-5-4대-핵심-실험-실측-데이터-empirical-benchmark-results)
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[-22c55e?style=for-the-badge)](#-6-초저전력-친환경-ai-연산-효율-지표-green-ai-metrics)
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[](#-4-하드웨어-및-로봇-플랫폼-호환성-매트릭스)
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[](./arduino_esp32_firmware.cpp)
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> **166,745개 전뇌 초파리 연결망 기반 다중 생체모방 로보틱스 및 Sim-to-Real 초저전력 임베디드 제어 피지컬 AI 파운데이션 모델.**
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> *[ 🌐 English Documentation ](README.md) | [ 🇰🇷 한국어 매뉴얼 ](README_KR.md) | [ 🎮 실시간 3D 웹 라이브 데모 ](https://huggingface.co/spaces/hwihwalab/neuro-robo-studio)*
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> [!TIP]
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| 파라미터 / 평가 항목 | 실측 사양 및 수치 (Empirical Result) | 아키텍처 및 연구 도메인 |
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| :--- | :--- | :--- |
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| **모델 공식 명칭** | `neuro-robo-connectome` | Physical AI, LeRobot, Connectome Robotics, 피지컬 AI, 뉴로모픽 |
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| **생체 모체 기원** |
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| **신경망 규모** | **166,745개 뉴런 ·
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| **신경 루프 지연시간** | **5.67 ms** (ORN ➔ ALPN ➔ DN ➔ MN 폐루프) | 초저지연 제어, 실시간 100Hz 모터 토크 생성 |
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| **전력 소모량** | **0.05 W** (MCU) vs **700 W** (클라우드 H100 GPU) | Green AI, 친환경 AI, 14,000배 전력 절감, 엣지 AI |
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| **제어 로봇 바디 (8종)**| **생체모방 로봇 8종** (CyberFly, Go1, G1, T1, MicroDuck, BH, Drone, AGV) | 6족 곤충, 4족 로봇개, 2족 휴머노이드, 마이크로 드론, AMR |
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## 📌 1. 모델 상세 개요 (Model Description)
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**
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본 모델은 클라우드 거대 언어/행동 모델(VLA/LLM) 대비 **1/14,000 이하의 초저전력(0.05W) 및 10ms 미만(실측 5.67ms)의 초저지연 폐루프 제어**를 달성하여, 휴머노이드, 4족보행 로봇개, 마이크로 드론 등 8종의 상이한 생체모방 로봇을 별도의 전이 재학습 없이도 실시간으로 자율 주행 및 장애물 회피를 수행하도록 제어합니��.
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# 🧠 뉴로-로보 커넥톰 | 생체모방 로보틱스를 위한 전뇌 피지컬 AI 파운데이션 모델
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[](README.md)
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[](README_KR.md)
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[](https://opensource.org/licenses/MIT)
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[](https://huggingface.co/lerobot)
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[%20%26%20FlyWire%20(139.2k)-10b981?style=for-the-badge)](https://janelia.org)
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[](#-5-4대-핵심-실험-실측-데이터-empirical-benchmark-results)
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[-22c55e?style=for-the-badge)](#-6-초저전력-친환경-ai-연산-효율-지표-green-ai-metrics)
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[](#-4-하드웨어-및-로봇-플랫폼-호환성-매트릭스)
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[](./arduino_esp32_firmware.cpp)
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> **166,745개 전뇌 초파리 연결망(수컷 MaleCNS 및 암컷 FlyWire FAFB) 기반 다중 생체모방 로보틱스 및 Sim-to-Real 초저전력 임베디드 제어 피지컬 AI 파운데이션 모델.**
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> *[ 🌐 English Documentation ](README.md) | [ 🇰🇷 한국어 매뉴얼 ](README_KR.md) | [ 🎮 실시간 3D 웹 라이브 데모 ](https://huggingface.co/spaces/hwihwalab/neuro-robo-studio)*
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> [!TIP]
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| 파라미터 / 평가 항목 | 실측 사양 및 수치 (Empirical Result) | 아키텍처 및 연구 도메인 |
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| :--- | :--- | :--- |
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| **모델 공식 명칭** | `neuro-robo-connectome` | Physical AI, LeRobot, Connectome Robotics, 피지컬 AI, 뉴로모픽 |
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| **생체 모체 기원** | 성체 초파리 중추신경계 전뇌 커넥톰 (수컷 MaleCNS & 암컷 FlyWire FAFB) | Nature 2026 MaleCNS, FlyWire, 구글 리서치, 자넬리아 |
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| **신경망 규모** | **166,745개 (수컷) / 139,255개 (암컷) 뉴런 · 275만~328만 개 시냅스 · 815개 운동 뉴런** | Spiking Neural Network (SNN), LIF 미분방정식 |
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| **신경 루프 지연시간** | **5.67 ms** (ORN ➔ ALPN ➔ DN ➔ MN 폐루프) | 초저지연 제어, 실시간 100Hz 모터 토크 생성 |
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| **전력 소모량** | **0.05 W** (MCU) vs **700 W** (클라우드 H100 GPU) | Green AI, 친환경 AI, 14,000배 전력 절감, 엣지 AI |
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| **제어 로봇 바디 (8종)**| **생체모방 로봇 8종** (CyberFly, Go1, G1, T1, MicroDuck, BH, Drone, AGV) | 6족 곤충, 4족 로봇개, 2족 휴머노이드, 마이크로 드론, AMR |
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## 📌 1. 모델 상세 개요 (Model Description)
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**Neuro-Robo Connectome Physical AI Foundation Model**은 세계 최대 규모의 초파리 중추신경계 전뇌 연결망(**수컷 MaleCNS: 166,745개 뉴런 및 암컷 FlyWire FAFB: 139,255개 뉴런, 2,753,975~3,280,000개 시냅스, 815개 척수 다리 운동 뉴런**)을 기반으로 설계된 **전뇌 뉴로모픽 피지컬 AI 파운데이션 모델**입니다.
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본 모델은 클라우드 거대 언어/행동 모델(VLA/LLM) 대비 **1/14,000 이하의 초저전력(0.05W) 및 10ms 미만(실측 5.67ms)의 초저지연 폐루프 제어**를 달성하여, 휴머노이드, 4족보행 로봇개, 마이크로 드론 등 8종의 상이한 생체모방 로봇을 별도의 전이 재학습 없이도 실시간으로 자율 주행 및 장애물 회피를 수행하도록 제어합니��.
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