Applied Intelligence for Physical AI
AIPA Lab is a research and experimentation laboratory dedicated to building intelligent physical systems that perceive, decide, and act in the real world. We integrate artificial intelligence, robotics, and digital twin technologies to enable reliable, autonomous, and scalable physical AI solutions.
Connecting Data → Intelligence → Action → Continuous Optimization
From Intelligence to Reliable Physical Behavior
AIPA Lab focuses on translating intelligent algorithms into reliable physical behavior. Our research bridges the gap between simulation, learning, and real-world deployment to ensure that AI systems perform safely and effectively in physical environments.
We emphasize hands-on experimentation, system-level integration, and deployable prototypes. Rather than focusing solely on theoretical models, we prioritize engineering validation and real-world applicability.
By combining artificial intelligence, control theory, robotics, and simulation technologies, we aim to create intelligent systems that continuously learn and adapt to dynamic environments.
Vision
To become a leading research laboratory in Physical AI and intelligent robotics for industrial and societal applications.
Mission
To develop, validate, and deploy applied intelligence systems that enhance autonomy, safety, and efficiency in real-world physical systems.
Research Focus Areas
We bridge simulation, learning, and real-world execution to deliver intelligent systems that operate reliably in physical environments.
Robot Manipulation & Embodied AI
Learning-based and model-based manipulation for robot arms in unstructured/semi-structured environments; vision-guided grasping; learning from demonstration; reinforcement learning; perception-action coupling.
Methods
Applications
Industrial assembly • Flexible packaging • Logistics automation • Service robotics
Physical AI Digital Twin
Physics-based digital twin platforms for simulation-driven learning and validation; rapid prototyping; sim-to-real transfer; performance optimization.
Methods
Applications
Robotic workcells • Manufacturing optimization • Virtual commissioning
Smart Factory Intelligence
Intelligent manufacturing systems integrating sensing, computation, and actuation; AI-driven production optimization; cyber-physical systems.
Methods
Applications
Automated production lines • Quality inspection • Energy management
Edge Physical AI Systems
Low-latency on-device intelligence; efficient model deployment; real-time decision making.
Methods
Applications
Mobile robots • AGV/AMR systems • Embedded robotics
Representative Projects
From simulation to deployment — applied intelligence in action
Vision-Based Robotic Grasping Prototype
PrototypeDevelop a vision-guided manipulation system for flexible object grasping.
Stack
Architecture
Perception → Grasp Planning → Motion Control → Feedback Loop
Robot Arm Sorting and Pick-and-Place Cell
Pilot DemoBuild an automated sorting system for mixed industrial components.
Stack
Architecture
Vision → Classification → Trajectory Planning → Execution
Physical AI Digital Twin Platform
BetaCreate a simulation-driven platform for robotic workcells.
Stack
Architecture
Simulation → Learning → Deployment → Validation
Edge AI Deployment for Industrial Robots
ExperimentalDeploy low-latency AI inference on embedded platforms.
Stack
Architecture
Sensor → Edge Inference → Control → Feedback
Laboratory Infrastructure & Platforms
Designed for rapid experimentation, system integration, and iterative testing of intelligent physical systems.
Hardware Platforms
- Industrial and collaborative robot arms
- Multi-camera vision systems
- Force and tactile sensors
- AGV and mobile robot platforms
- Edge AI computing devices
Software Stack
- ROS2 middleware
- NVIDIA Isaac Sim
- Digital twin frameworks
- AI training pipelines
- Monitoring dashboards
Lab Facilities
- Robotic workcells
- Simulation clusters
- Testing and validation zones
- Safety monitoring systems
Research Workflow & Activities
Problem Definition
Simulation & Modeling
Algorithm Development
System Integration
Physical Deployment
Performance Evaluation
Current Activities
- Robotic manipulation experiments
- Sim-to-real validation studies
- Prototype demonstrations
- Digital twin testing
- Internal workshops
- Technical seminars
AIPA Lab organizes regular training programs on robotics, simulation, and AI engineering for students and researchers.
Open Research Resources
Available Materials
- Technical documentation
- Experiment logs
- Demo videos
- System walkthroughs
- Presentation slides
AIPA Lab follows open science and reproducibility principles, ensuring transparent documentation and version control.
Collaboration & Partnership Framework
We provide technical consulting, system prototyping, and technology transfer support for partners.
Joint Academic Research
Collaborative research projects with universities and institutes
Industry Proof-of-Concept
Industry-oriented proof-of-concept development and validation
Student Programs
Student internships and thesis supervision opportunities
Pilot Deployments
Pilot industrial deployments and technology demonstrations
Collaboration Principles