Mathematical Models Using Artificial Intelligence for Surveillance Systems

12A Novel Zone Segmentation (ZS) Method for Dynamic Obstacle Detection and Flawless Trajectory Navigation of Mobile Robot

Rapti Chaudhuri*, Jashaswimalya Acharjee and Suman Deb

Department of CSE, National Institute of Technology, Agartala, India

Abstract

Simultaneous Localization and Mapping (SLAM) is foremost for consistent navigation with proficient recognition of possible obstacles by an Automated Guided Vehicle (AGV). The basic need of the research work for dynamic obstacle detection and flawless trajectory navigation of mobile robot is to enable an automated guided mobile robot which would be able to make decision to choose its path by accumulating motion plan with the help of actuated sensors. It is noticed that the possible on-route navigation and obstacle identification mechanism has its own limitations and challenges. Visual presentation and inference of perceived data for significant concern. The algorithms for combining the Light Detection and Ranging (LiDAR) data, Inertial Measurement Unit (IMU) data, and Multiple Optical sensors to create co-visibility, is an organized method of presenting surrounding data. It is evident from a literature survey that standardized particle filter, feature matching, and Monte Carlo Localization have proved to be noteworthy in both formation of traversal map as well as robot pose estimation. Keeping those techniques as reference, the present work establishes a novel method for performing optimized point-to-point navigation. The main ...