Influence of data clouds fusion from 3D real-time vision system on robotic group dead reckoning in unknown terrain

This paper proposes the solution of tasks set required for autonomous robotic group behavior optimization during the mission on a distributed area in a cluttered hazardous terrain. The navigation scheme uses the benefits of the original real-time technical vision system &#x0028 TVS &#x0029 b...

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Bibliographic Details
Published in:IEEE/CAA journal of automatica sinica 2020-03, Vol.7 (2), p.368-385
Main Authors: Ivanov, Mykhailo, Sergyienko, Oleg, Tyrsa, Vera, Lindner, Lars, Flores-Fuentes, Wendy, Rodriguez-Quinonez, Julio Cesar, Hernandez, Wilmar, Mercorelli, Paolo
Format: Article
Language:English
Subjects:
Approximation
Data exchange
Dead reckoning
Energy conservation
Fuzzy logic
Hazardous areas
Machine vision
Motion planning
Optimization
Post-processing
Real time
Robot kinematics
Robotics
Surface emitting lasers
Task analysis
Terrain
Three-dimensional displays
Trajectory planning
Triangulation
Vision systems
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Summary:This paper proposes the solution of tasks set required for autonomous robotic group behavior optimization during the mission on a distributed area in a cluttered hazardous terrain. The navigation scheme uses the benefits of the original real-time technical vision system &#x0028 TVS &#x0029 based on a dynamic triangulation principle. The method uses TVS output data with fuzzy logic rules processing for resolution stabilization. Based on previous researches, the dynamic communication network model is modified to implement the propagation of information with a feedback method for more stable data exchange inside the robotic group. According to the comparative analysis of approximation methods, in this paper authors are proposing to use two-steps post-processing path planning aiming to get a smooth and energy-saving trajectory. The article provides a wide range of studies and computational experiment results for different scenarios for evaluation of common cloud point influence on robotic motion planning.
ISSN:2329-9266
2329-9274
DOI:10.1109/JAS.2020.1003027