Solutions

Mobilio NavigateX – Digital Twin & AI Navigation Platform

NavigateX is Mobilio’s next-generation digital twin navigation platform, fusing LiDAR, IMU, and 360° camera data to generate high-precision 3D maps and real-time path optimization.

Digital Twin Mapping: Creates detailed 3D digital twins of factories, logistics hubs, shipyards, and airports
AI Path Planning: AI-powered route optimization and autonomous navigation
BIM & GIS Integration: Connects seamlessly with BIM models and platforms like Google or Naver Maps
Cloud & Edge Ready: Enables remote management, monitoring, and collaborative mapping

Applications: Smart logistics, shipbuilding & construction, hazardous zone safety, infrastructure management

Mobilio 360 Twin - Digtal Twin

360 Twin uses 360° cameras and sensor data to reproduce immersive, street-view–like digital twins of real-world environments.

Immersive Mapping: Captures and stores every angle of the site in 360°
BIM Comparison: Accurately compares construction drawings with on-site progress
Remote Inspection: Enables real-time site monitoring from anywhere
AI Recognition: Supports object recognition, asset management, and anomaly detection

Applications: Construction & plant management, safety inspection, facility asset management, remote collaboration

Autonomous Robots

Autonomous Robots are machines capable of making decisions and moving independently using a combination of sensors, AI, and navigation algorithms.
Core functions:
- Perception – sensing and understanding the environment
- Decision-making – AI-driven path planning and task selection
- Control – executing movement and actions via motors/actuators
Applications: logistics (delivery robots), manufacturing (smart factories), construction & shipbuilding (hazard inspection), disaster response (search & rescue).

SLAM & Navigation

SLAM (Simultaneous Localization and Mapping) enables robots to localize themselves while building a map of the environment at the same time.
It leverages LiDAR, cameras, IMUs, and sensors to allow robots to operate even in GPS-denied or complex environments.
Navigation is the process of using SLAM-generated maps to plan optimal paths, avoid obstacles, and reach destinations safely.

AI Logis

Mobilio Logis is an intelligent robotic solution that automates transportation, sorting, and loading tasks in logistics environments.

Autonomous Navigation: LiDAR- and SLAM-based navigation for safe movement in complex warehouses
Smart Handling: Integration with robotic arms for automated picking, stacking, and unloading
IoT Connectivity: Links with sensors and WMS (Warehouse Management Systems) for real-time inventory and flow control
Cloud Management: Remote monitoring and data-driven operational optimization
Applications: Smart warehouses, in-factory material transport, e-commerce fulfillment centers, large-scale distribution networks

Wireless IIoT Sensor

Mobilio’s IoT sensor solutions provide real-time data collection and management across diverse environments.
- Environmental Sensors: Gas, temperature, humidity, oxygen monitoring
- 360° Camera & LiDAR: Digital twin creation of physical spaces
- Vibration & Position Sensors: Equipment monitoring and predictive maintenance
- Applications: Smart factories, safety management, remote monitoring, asset management

AI Insightor

Mobilio’s AI solutions empower robots and digital twins with intelligent decision-making and automation.

AI Vision Recognition: Object detection, obstacle avoidance, safety monitoring
AI Navigation: SLAM-based path planning and autonomous driving
AI Analytics Platform: Equipment anomaly detection, risk prediction, productivity optimization
Applications: Smart logistics, construction & shipbuilding, energy plants, disaster response

Mobilio Reinforcement Learning

Mobilio leverages Reinforcement Learning (RL) to enable robots to self-learn and optimize decision-making strategies.

Simulation-Based Training: Safe and rapid learning through thousands of trials in digital twin environments
Reward-Driven Optimization: Rewards for successful actions and penalties for failures to improve performance
Sim-to-Real Transfer: Applying simulation-trained models directly to physical robots for faster adaptation
Applications:
- Path optimization in logistics robots
- Balance and obstacle negotiation in quadruped robots
- Task execution in humanoid robots
- Risk-avoidance behaviors in disaster-response robots