In this paper, a decentralized platform for simultaneous localization and mapping (SLAM) with multiple robots is developed. Each robot performs single robot view-based SLAM using an extended Kalman filter to fuse data from two encoders and a laser ranger. To extend this approach to multiple robot SLAM, a novel occupancy grid map fusion algorithm is proposed. Map fusion is achieved through a multistep process that includes image preprocessing, map learning (clustering) using neural networks, relative orientation extraction using norm histogram cross correlation and a Radon transform, relative translation extraction using matching norm vectors, and then verification of the results. The proposed map learning method is a process based on the self-organizing map. In the learning phase, the obstacles of the map are learned by clustering the occupied cells of the map into clusters. The learning is an unsupervised process which can be done on the fly without any need to have output training patterns. The clusters represent the spatial form of the map and make further analyses of the map easier and faster. Also, clusters can be interpreted as features extracted from the occupancy grid map so the map fusion problem becomes a task of matching features. Results of the experiments from tests performed on a real environment with multiple robots prove the effectiveness of the proposed solution.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Face Frontalization Using an Appearance-Flow-Based Convolutional Neural Network ABSTRACT: Face recognition (FR) is a difficult problem because of the wide range of facial expressions. Non-frontal faces can be transformed
PROJECT TITLE : Mutual Component Convolutional Neural Networks for Heterogeneous Face Recognition ABSTRACT: For example, the goal of heterogeneous face recognition (HFR) is to recognise people in photos that are both visible and
PROJECT TITLE : Single Image Reflection Removal Using Convolutional Neural Networks ABSTRACT: Specular reflection occurs when individuals photograph through glass, obscuring the view behind the glass. Most investigations have
PROJECT TITLE : Model Reference Neural Adaptive Control Based BLDC Motor Speed Control ABSTRACT: A multi-variable, non-linear, strong-coupling system is employed in the brushless DC (BLDC) motor control system to show resilient
PROJECT TITLE :High Voltage Gain Interleaved Boost Converter with Neural Network Based MPPT Controller for Fuel Cell Based Electric Vehicle ApplicationsABSTRACT:Due to the additional vigorous regulations on carbon gas emissions

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry