•  
  •  
 

Abstract

With the increasing use of robotic networks, communication issues such as maintaining connections between nodes are becoming more prevalent. While previous routing protocols for wireless networks have been developed, they tend to address routing and link maintenance separately. Consequently, leading to increased costs and delays in network communication. Existing routing protocols typically focus on discovering links, connecting them, finding the most efficient path, and reducing costs associated with the path. However, their limitations have led to the development a new routing mechanism for robotic networks called Meta-Routing. Meta-Routing builds on existing routing protocols by incorporating regular routing of packets and maintenance of links in mobile agent environments. This approach aims to improve efficiency and reduce routing and link maintenance costs. In addition, meta-Routing seeks to minimize communication path costs and the overhead cost associated with discovering a route, repairing a link, or creating a new communication path among nodes. This paper presents a method for achieving Meta-Routing by controlling robot motion based on recognizing the radio frequency (RF) environment through Hidden Markov Models (HMMs) and gradient descent methods. Simulation results show that Meta-Routing, based on controlling individual robot motion, can provide self-healing capabilities in mobile robot networks, decrease network latency, and improve network performance.

Download

Share

COinS