Development of an Advanced Navigation System for Autonomous Mobile Robots for Logistics Environments

In this paper, we proposes the development of a novel navigation system for Autonomous Mobile Robots (AMR) in a logistics environment. AMR aim to provide a more flexible and innovative solution compare with traditional Automated Guided Vehicle (AGV) systems, in order to alleviate the inconvenience o...

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Bibliographic Details
Main Authors: Choi, Jun-Hyeon, Bae, Sang-Hyeon, An, Ye-Chan, Kuc, Tae-Yong
Format: Conference Proceeding
Language:English
Subjects:
Autonomous Mobile Robots
Feature extraction
Localization
Navigation
Navigation system
Obstacle detection
Path planning
Productivity
Robot sensing systems
Semantics
Sensor phenomena and characterization
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Summary:In this paper, we proposes the development of a novel navigation system for Autonomous Mobile Robots (AMR) in a logistics environment. AMR aim to provide a more flexible and innovative solution compare with traditional Automated Guided Vehicle (AGV) systems, in order to alleviate the inconvenience of line reconfiguration due to environmental changes. AMR equipped with various functionalities and sensors play a significant role in automating logistics and factory operations.The proposed navigation system includes methods for optimal path planning for single or multiple robots in a warehouse environment, improved localization techniques, and obstacle detection methods. By utilizing three maps, the system plans specialized paths for logistics warehouses, and addresses the limitations of conventional probability-based localization methods by utilizing semantic features extracted from the radar sensor for position recognition.Furthermore, this system incorporates LIDAR sensors for obstacle detection and ensures that the robot stops when obstacles are detected within the predicted area based on size and speed. The implementation of this navigation system enhances the autonomy and efficiency of AMR in logistics environments, improving position measurement, path planning, and obstacle detection capabilities. It offers the potential for increased productivity and cost savings in automated logistics system operations
ISSN:2642-3901
DOI:10.23919/ICCAS59377.2023.10316962