Noble Approach on Sensor Fused Bio Intelligent Path Optimisation and Single Stage Obstacle Recognition in Customized Mobile Agent

Optimized PTP (Point to Point) Navigation by customized mobile agent constitutes extensive research domain in Machine Intelligence. Distinct Literature survey confirms the proposal of SLAM (Simultaneous Localization And Mapping) mediated sensor usage for visual data collection in a particular GPS (G...

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Bibliographic Details
Published in:Procedia computer science 2023, Vol.218, p.778-787
Main Authors: Chaudhuri, Rapti, Deb, Suman, Das, Hillol
Format: Article
Language:English
Subjects:
Bio Intelligent path planning approach
Fusion SLAM
GPS-denied
Machine Intelligence
MRN (Mobile Robot Navigation)
PTP (Point To Point) Navigation
SLAM (Simultaneous localization And Mapping)
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Summary:Optimized PTP (Point to Point) Navigation by customized mobile agent constitutes extensive research domain in Machine Intelligence. Distinct Literature survey confirms the proposal of SLAM (Simultaneous Localization And Mapping) mediated sensor usage for visual data collection in a particular GPS (Global Positioning System) - denied indoor environment. This has been further followed by fused data collection using multi sensor for obtaining long time and high precision localization and obstacle detection in MRN (Mobile Robot Navigation). This paper proposes an idea to incorporate machine learning module for data modeling so that the obstacle detection and identification results in relatively more precise, accurate and efficient. The comparative numerical analysis has been presented to establish the proposed methodology. Along with this, Fusion SLAM algorithm has been created and proposed which combines features of both 2D LiDAR (Light Detection And Ranging) and RGB-D (Red, Green, Blue Depth) SLAM, resulting in visual reference of combined detected periphery and reconstructed 3D depth of on-path obstacles. The aforesaid procedure is further extended with integration of Bio Intelligent path planning approach. Experimental analysis carried out with sample candidate functions with respect to concerned mobile robot and considered indoor environment has been presented which would prove to be important citation for further research in the domain of collision-free optimum MRN.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2023.01.058