TonyleeKorea Project Documentation

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Nvidia AGX Xavier and Thumper RC Rover

Hardware Specifications

Type	Details	Type	Details
frame	Custom carbon fiber chassis	FC	Nvidia AGX Xavier Developer Kit
motor	4x brushless DC motors	ESC	30A ESC with regenerative braking
RC	2.4GHz DSSS radio	mode	Autonomous/Manual hybrid
weight	3.2kg with battery	class	Research/Development platform
battery	6S LiPo 5000mAh	air-time	45 minutes continuous operation
configurator	Custom ROS2 interface	last updated	July 10, 2021

Project Integration with GitHub Repositories

AI-Assisted Infrastructure Inspection

Repository: AI-Assisted-Inspection

This project leverages Xavier’s computing power for Mixed Reality infrastructure inspection:

# Xavier-powered inspection system
import tensorrt as trt
import cv2
import numpy as np

class XavierInspectionAI:
    def __init__(self):
        self.vision_model = self.load_optimized_model()
        self.ar_overlay = AROverlaySystem()
    
    def analyze_structure(self, camera_feed):
        # Real-time structural analysis
        defects = self.vision_model.detect_anomalies(camera_feed)
        ar_annotations = self.ar_overlay.generate_markers(defects)
        return {"defects": defects, "ar_data": ar_annotations}

3D Printed Drone Assembly Integration

Repository: 3D-Printed-Drone-Assembly

Custom rover-drone coordination system:

Autonomous Navigation: Xavier processes LiDAR and camera data for path planning
Drone Coordination: Communication with autonomous drones for area mapping
Real-time Processing: 30 TOPS AI performance for simultaneous localization and mapping (SLAM)

Performance Specifications

Computing Performance

AI Performance: 32 TOPS (Tera Operations Per Second)
GPU: 512-core Volta GPU with Tensor Cores
CPU: 8-core ARM v8.2 64-bit CPU
Memory: 32GB 256-bit LPDDR4x
Storage: 32GB eUFS 2.1

Power Efficiency

Software Stack

Operating System & Frameworks

# JetPack 5.1 installation
sudo apt update
sudo apt install nvidia-jetpack

# Deep learning frameworks
pip3 install torch torchvision
pip3 install tensorflow-gpu
pip3 install onnxruntime-gpu

# ROS2 for robotics
sudo apt install ros-galactic-desktop

Custom Applications

Thumper Rover Control System

# Rover control with Xavier integration
import rclpy
from geometry_msgs.msg import Twist
from sensor_msgs.msg import Image, PointCloud2

class ThumperController:
    def __init__(self):
        self.xavier_ai = XavierAIProcessor()
        self.navigation = AutonomousNavigation()
        
    def process_sensor_data(self, lidar_data, camera_data):
        # Xavier AI processing
        obstacles = self.xavier_ai.detect_obstacles(camera_data)
        path = self.navigation.plan_path(lidar_data, obstacles)
        return self.generate_control_commands(path)

Mixed Reality Integration

# AR overlay for infrastructure inspection
class MixedRealityInspection:
    def __init__(self):
        self.xavier_inference = XavierAI()
        self.hololens_interface = HoloLensAPI()
        
    def real_time_inspection(self, structure_scan):
        # Process with Xavier AI
        analysis = self.xavier_inference.structural_analysis(structure_scan)
        
        # Generate AR overlays
        ar_markers = self.generate_defect_markers(analysis)
        self.hololens_interface.display_overlays(ar_markers)

Integration with Other AIOT Projects

Digital Twin System

Repository: battery_digital_twin

Xavier processes real-time battery telemetry for digital twin modeling:

# Battery digital twin with Xavier processing
class BatteryDigitalTwin:
    def __init__(self):
        self.xavier_ml = XavierMLProcessor()
        self.uncertainty_model = UncertaintyQuantification()
        
    def update_twin(self, battery_telemetry):
        # Real-time state estimation
        state = self.xavier_ml.predict_battery_state(battery_telemetry)
        uncertainty = self.uncertainty_model.calculate_bounds(state)
        return {"state": state, "confidence": uncertainty}

Drone Coordination Network

Repository: bebop_autonomy

Pixhawk Flight Controller

Xavier serves as ground control for autonomous drone fleet:

Mission Planning: Real-time path optimization for multiple drones
Computer Vision: Object detection and tracking coordination
Communication Hub: 5G/WiFi coordination between rover and drone fleet

Development Environment

Docker Containerization

# Xavier development container
FROM nvcr.io/nvidia/l4t-ml:r35.2.1-py3

# Install custom dependencies
RUN apt-get update && apt-get install -y \
    ros-galactic-desktop \
    python3-opencv \
    librealsense2-dev

# Copy application code
COPY ./thumper_control /app/thumper
COPY ./ai_inspection /app/inspection

WORKDIR /app
CMD ["python3", "main.py"]

Real-time Performance Monitoring

# Xavier performance monitoring
import jetson.inference
import jetson.utils

class XavierMonitor:
    def __init__(self):
        self.stats = jetson.utils.cudaDeviceGetMemoryInfo()
        
    def get_performance_metrics(self):
        return {
            "gpu_utilization": self.get_gpu_usage(),
            "memory_usage": self.get_memory_stats(),
            "temperature": self.get_thermal_status(),
            "power_consumption": self.get_power_draw()
        }

Tags:

Nvidia Xavier