Home / Computer Science / Robust communication for location-aware mobile robots using motes

Robust communication for location-aware mobile robots using motes

 

Table Of Contents


Project Abstract

The best mode of communication for a team of mobile robots deployed to cooperatively perform a particular task is through exchange of messages. To facilitate such exchange, a communication network is required.

When successful execution of the task hinges on communication, the network needs to be robust – sufficiently reliable and secure. The absence of a fixed network infrastructure defeats the use of traditional wire-based communication strategies or an 802.11-based wireless network that would require an access point. In such a case, only an ad hoc wireless network is practical.

This project presents a robust wireless communication solution for mobile robots using motes. Motes, sometimes referred to as smart dust, are small, low-cost, low-power computing devices equipped with wireless communication capability that uses Radio Frequency (RF). Motes have been applied widely in wireless sensing networks and are typically connected to sensors and used to gather information about their environment. Communication in a mote network is inherently unreliable due to message loss, exposed to attacks, and supports very low bandwidth. Additional mechanisms are therefore required in order to achieve robust communication.

Multi-hop routing must be used to overcome short signal transmission range. The ability of a mobile robot to determine its present location can be exploited in building an appropriate routing protocol. When present, information about a mobile robot’s future location can aid further the routing process. To guarantee message delivery, a transport protocol is necessary. Optimal packet sizes should be chosen for best network throughput. To protect the wireless network from attacks, an efficient security protocol can be used.

This thesis describes the hardware setup, software configuration, and a network protocol for a team of mobile robots that use motes for robust wireless communication. The thesis also presents results of experiments performed.


Project Overview

Blazingprojects Mobile App

πŸ“š Over 50,000 Project Materials
πŸ“± 100% Offline: No internet needed
πŸ“ Over 98 Departments
πŸ” Software coding and Machine construction
πŸŽ“ Postgraduate/Undergraduate Research works
πŸ“₯ Instant Whatsapp/Email Delivery

Blazingprojects App

Related Research

Computer Science. 4 min read

Predicting Disease Outbreaks Using Machine Learning and Data Analysis...

The project topic, "Predicting Disease Outbreaks Using Machine Learning and Data Analysis," focuses on utilizing advanced computational techniques to ...

BP
Blazingprojects
Read more β†’
Computer Science. 3 min read

Implementation of a Real-Time Facial Recognition System using Deep Learning Techniqu...

The project on "Implementation of a Real-Time Facial Recognition System using Deep Learning Techniques" aims to develop a sophisticated system that ca...

BP
Blazingprojects
Read more β†’
Computer Science. 2 min read

Applying Machine Learning for Network Intrusion Detection...

The project topic "Applying Machine Learning for Network Intrusion Detection" focuses on utilizing machine learning algorithms to enhance the detectio...

BP
Blazingprojects
Read more β†’
Computer Science. 3 min read

Analyzing and Improving Machine Learning Model Performance Using Explainable AI Tech...

The project topic "Analyzing and Improving Machine Learning Model Performance Using Explainable AI Techniques" focuses on enhancing the effectiveness ...

BP
Blazingprojects
Read more β†’
Computer Science. 3 min read

Applying Machine Learning Algorithms for Predicting Stock Market Trends...

The project topic "Applying Machine Learning Algorithms for Predicting Stock Market Trends" revolves around the application of cutting-edge machine le...

BP
Blazingprojects
Read more β†’
Computer Science. 3 min read

Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems...

The project topic, "Application of Machine Learning for Predictive Maintenance in Industrial IoT Systems," focuses on the integration of machine learn...

BP
Blazingprojects
Read more β†’
Computer Science. 3 min read

Anomaly Detection in Internet of Things (IoT) Networks using Machine Learning Algori...

Anomaly detection in Internet of Things (IoT) networks using machine learning algorithms is a critical research area that aims to enhance the security and effic...

BP
Blazingprojects
Read more β†’
Computer Science. 4 min read

Anomaly Detection in Network Traffic Using Machine Learning Algorithms...

Anomaly detection in network traffic using machine learning algorithms is a crucial aspect of cybersecurity that aims to identify unusual patterns or behaviors ...

BP
Blazingprojects
Read more β†’
Computer Science. 4 min read

Predictive maintenance using machine learning algorithms...

Predictive maintenance is a proactive maintenance strategy that aims to predict equipment failures before they occur, thereby reducing downtime and maintenance ...

BP
Blazingprojects
Read more β†’
WhatsApp Click here to chat with us