3D Optical Machine Vision Sensors With Intelligent Data Management for Robotic Swarm Navigation Improvement

Abstract

The optimized communication within robotic swarm, or group (RG) in a tightly obstacled ambient is crucial point to optimize group navigation for efficient sector trespass and monitoring. In the present work the main set of problems for multi-objective optimization in a non-stationary environment is described. It is presented the algorithm of data transfer from 3D optical sensor, based on the principle of dynamic triangulation. It uses the distributed scalable big data storage and artificial intelligence in automated 3D metrology. Two different simulations in order to optimize the fused data base for better path planning aiming the improvement of electric wheeled mobile robots group navigation in unknown cluttered terrain is presented. The optical laser scanning sensor combined with Intelligent Data Management permits more efficient dead-reckoning of the RG.