CAD2SLAM: Adaptive Projection Between CAD Blueprints and SLAM Maps

Robotic mobile platforms are key building blocks for numerous applications and cooperation between robots and humans is a key aspect to enhance productivity and reduce labor cost. To operate safely, robots typically rely on a custom map of the environment that depends on the sensor configuration of...

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Bibliographic Details
Published in:IEEE robotics and automation letters Vol. 10; no. 2; pp. 1529 - 1536
Main Authors: Bayon-Gutierrez, Martin, Prieto-Fernandez, Natalia, Garcia-Ordas, Maria Teresa, Benitez-Andrades, Jose Alberto, Alaiz-Moreton, Hector, Grisetti, Giorgio
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.02.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Accuracy
Adaptive systems
Algorithms
Collaboration
computational geometry
Floors
Location awareness
mapping computational geometry
Morphing
Navigation
Pipelines
Platforms
Representations
Robot control
Robot sensing systems
Robotics
Robots
Simultaneous localization and mapping
Software architecture for robotic and automation
Solid modeling
ISSN:2377-3766, 2377-3766
Online Access:Get full text
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Summary:Robotic mobile platforms are key building blocks for numerous applications and cooperation between robots and humans is a key aspect to enhance productivity and reduce labor cost. To operate safely, robots typically rely on a custom map of the environment that depends on the sensor configuration of the platform. In contrast, blueprints stand as an abstract representation of the environment. The use of both CAD and SLAM maps allows robots to collaborate using the blueprint as a common language, while also easing the control for non-robotics experts. In this work we present an adaptive system to project a 2D pose in the blueprint to the SLAM map and vice-versa. Previous work in the literature aims at morphing a SLAM map to a previously available map. In contrast, CAD2SLAM does not alter the internal map representation used by the SLAM and localization algorithms running on the robot, preserving its original properties. We believe that our system is beneficial for the control and supervision of multiple heterogeneous robotic platforms that are monitored and controlled through the CAD map. Finally, we present a set of experiments that support our claims as well as open-source implementation.
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ISSN:2377-3766
2377-3766
DOI:10.1109/LRA.2024.3522838