Use Case: Interact with different real world objects Approximation Problem: Items have a complex shape in 3 dimensions
OMiLab Robotic Arm 1
Use Case: Assemble a product by incorporating components Planning Problem: Reaching the goal state in a complex environment
OMiLab Robotic Arm 2
Use Case: Capture characteristics of a system without irrelevant details Modeling Problem: Finding the right degree of domain-specificity
OMiLab Robotic Car PoC 1
Use Case: Enable new experiences for users with context aware devices Sensor Fusion Problem: Integrate sensor information in a consistent model
OMiLab Robotic Car PoC 2
The aim of this project is to automatically provide a list of cars for a specific type of character (business man, worker etc.). The cars are selected according to the preferences of the selected character.
The aim of this project is the integration of physical and model environment within a SmartCity Scenario. ADOxx http requests are used to establish a connection between smart city model and MBots.
Smart City CPS Integration
Smart-Home Supply Chain
The project models a real life cross-road and simulates a new Smart Light Infrastructure by calculating the priorities of each street.The project aims to reduce the time spent in the cross-road as an everyday problem.
Smart Street Lights
The aim of this project is a smart tourguide who goes through a physical world with attractions, which you modelled before and gives you information about it by image recognition.
This project combines a user-generated model of a greenhouse with multiple sensor inputs and a rule-based-system to enable an ideal environment for various crops.
Smart Urban Farming
Use Case: Selbstidentifikation eines CPS sowie dessen Darstellung und experimentelle Möglichkeiten mittels ADOxx
This service reliefs airport customers from the burden of the baggage. The baggage is picked up at the customer's house and delivered directly to the airport. The weight is already determined on the way.
The Smart Drone Tourist Guide is an autonomous drone which accompanies a user on a sightseeing tour.
Smart Drone Tourist Guide
Use Case: Simulation of a delivery process in warehouses Ontology: Semantic Annotations using the SeMFIS modelling toolkit
OMiLAB Robotic Arm & Car Experiment 1
Use Case: Learn and play a simple piano song. Genetic Algorithm: Learning the keys in the correct order
OMiLAB Robotic Arm Experiment 1
Use Case: Construct a domain-specific modeling method Metamodeling: Service-based ADOxx extension with scripts
OMiLAB Robotic Arm Experiment 2
Use Case: Mixing a cocktail by receiving speech input Integration: Combine different technologies, models and methods
OMiLAB Robotic Arm Experiment 3
Use Case: Towers of hanoi with three discs Constraint Satisfaction: Formalize the puzzle as a Constraint Satisfaction Problem
OMiLAB Robotic Arm & Car Experiment 4
Use Case: Conceptual model of communication Metamodeling: New Library in Adoxx including GraphReps
OMiLAB Robotic Car Experiment 1
Use Case: Autonomous movement of robots Fuzzy Logic: Handle fuzzy sensor data input
OMiLAB Robotic Car Experiment 2
Use Case: Autonomous parking of vehicles Service-driven Enrichment: Model-based service extension
OMiLAB Robotic Car Experiment 3
Use Case: A smart assistant for model model interaction and cyber-physical systems Communication Problem: Support cps2human interaction through NAO
CPS interaction with NAO
Use Case: Paint graphrep as scalable SVG image Rule Engine: Parse XML markup and control actuators
OMiLAB Robotic Spider Experiment 1
Use Case: Control robots with gestures Computer Vision: Learn and interpret gestures to carry out specific actions
Gesture-based Interaction with Cyber Physical Systems
Use Case: CPS movement within an environment which uses a tag based object location identification Image Recognition: Video based coordinates and object assessment
MBot Path Finder
Use Case: Coordinating CPSs in a delivery on demand production line
Communication Problem: cps2cps and cps2human communication
Delivery on Demand in a Cyber Physical System Production Line
Automization of the order preparation process in a warehouse using robotic workers.
Robotic Order Preparation
Use Case: A robot interprets the mood of a conversation. Sentiment analysis: Interprets emotions
Sentiment analysis with NAO
Providing a modelling method to manage and organize a self-driving vehicle for package delivery, as well as planning the most efficient route.
Smart Package Delivery with ADOxx
Use Case: Analyse a table soccer game
Image Recognition: Detect a specific object
Image Recognition - Table Soccer
The project aims to demonstrate a smart garden enviorment where different agents interact with different object. The data of different RFID sensors are used as input for a rule engine, which executes the appropriate rule.
Use Case: Collision prevention for MBots in a factory of the future. Sensor based detection of obstacles and MBOTs
MBOT Collision Prevention
This project is based on the sIOT framework and smart models. The aim is to model CPS environments that can be easily understood by humans and processable by machines. Other models must be aware of the CPS environment and take decisions accordingly.
CPS Environment Modelling
With "Energy Blockchain Control" the User is able to model his Smart Home and set preferences for Energy Controlling and Trading within a peer to peer Network.
ENERGY BLOCKCHAIN CONTROL
Errors in the execution of the model can be hard to detect. This project uses ontologies to store the informations about possible errors.
Use Case: Route planning and picking job execution in warehouse environments.
Genetic Algorithm: Metamodel based optimal picking job planning, execution, and simulation.
XST iRobot - OMiLAB Robotic Picking and Path Finding Experiment
Modify Scene2Model models via speech input and voice control.
Scene2Model Voice Control
Automatically create Capabilities from Components, as well as Components from Capabilities for s*Iot methodology.
The objective of the OMiLAB-Rob project is to integrate conceptual models (which are constructed by humans for humans) with cyber-physical systems. Thereby, the focus is to enable a knowledge-based understanding of "smart" models by machines. To facilitate the engineering of these systems, the OMiLAB-Rob project provices a physical and virtual environment, where experiments validate the integration of conceptual models and cyber-physical systems. In a continuous cycle, the experiments' results are used to refine the necessary methods.
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