Combining Data for Floor Plans
                     Combining Data 
for Floor Plans
Exploring methods for robotic environment perception and mapping.
Introduction
This presentation explores innovative methods for 
capturing data to construct accurate floor plans using 
robotic technology. We will look into various types of 
sensors, data collection techniques, and the role of active 
illumination in enhancing data quality.
01
Data Capture
Types of 
sensors used
The primary sensors involved in this method 
include imaging sensors for visual data and 
movement sensors for tracking navigation. 
Imaging sensors capture the environment's visual 
aspects, while movement sensors provide critical 
data on the robot's position and movement, 
creating a comprehensive data set for floor plan 
construction.
Data 
collection 
methods
Data collection occurs through continuous 
monitoring as the robot moves within the 
environment. This involves the real-time 
gathering of images and movement data, 
allowing the robot to perceive and construct a 
model of the environment. The integration of 
data from different sensor types enhances the 
accuracy and detail of the captured model.
Role of active 
illumination
Active illumination significantly enhances the 
quality of data captured by imaging sensors. By 
providing controlled lighting, it improves visibility 
and reduces shadows in the captured images. This 
allows for better feature recognition and accurate 
environmental modeling. Additionally, active 
illumination helps in capturing consistent data 
under varying lighting conditions, ensuring that the 
model built from such data is reliable and detailed.
02
Model Construction
Data processing 
techniques
Once data is collected, it undergoes various 
processing techniques to create a coherent model of 
the environment. This includes filtering noise from 
sensor data, aligning images, and integrating 
movement data to accurately map the space. 
Advanced algorithms are employed to analyze the 
data, reconstructing a detailed three-dimensional 
model of the environment that reflects real-world 
dimensions and features.
Storing the 
environment model
The constructed model of the environment needs to be stored 
efficiently for future access and use. Typically, this model is stored in 
a digital format within the robot's memory or on a cloud-based 
system. This allows for quick retrieval and use in different 
applications, such as navigation, obstacle avoidance, and more 
detailed analyses of the environment. The storage system must also 
allow for easy updates as the robot collects more data.
Transmitting to 
smartphone 
applications
For practical applications, the stored model can be transmitted 
to smartphone applications, allowing users to visualize the 
captured data. The transmission process involves sending data 
using wireless protocols, which enables real-time updates and 
interaction with the model. Users can manipulate the model on 
their smartphones for various purposes, such as planning, 
analysis, or more advanced robotics tasks like autonomous 
navigation.
Conclusions
In conclusion, the integration of various data 
collection techniques, sensor types, and active 
illumination plays a vital role in accurately 
constructing floor plans in robotic applications. 
The methods discussed showcase how 
technology can enhance user interactions with 
modeled environments, paving the way for 
future advancements in robotics and 
automation.
Thank 
you!
Do you have any questions?
Find more info here: 
https://patents.justia.com/patent/1209
4145