Volume V | Issue 7 | 2026 | Paper ID: IJATEM-V05I07P5

Transformer-Assisted Robotic MANET Routing for Disaster Response Using Secretary Bird Optimization

Author(s)

P. Manikandan, D. Lakshmi, E. Immanuvel Bright

Abstract

Rapid and reliable communication are important for Disaster Response (DR), where existing communication infrastructure become severely degraded. However, robotic Mobile Ad Hoc Networks (MANET) deployed in disaster environments face dynamic topology changes, unstable communication links, limited residual energy, node mobility, congestion, and frequent route failures. To overcome these issues, this paper proposes a Transformer-Assisted Robotic MANET Routing framework for DR using Secretary Bird Optimization (SBO). The collected MANET data is delivered to SBO module, which identifies suitable candidate relay robots by evaluating their fitness and jointly optimizing robot selection and energy-aware routing decisions. Subsequently, a Robotic Cluster formation layer selects appropriate leader robots, assigns relay nodes, and establishes a reliable communication backbone among the robotic agents. A Transformer Learning Module is then employed to extract significant network features through attention-based learning and model the temporal dependencies of changing network states for route prediction. Experimental result is implemented in OMNet++, the effectiveness of the proposed framework is assessed using Packet Delivery Ratio (PDR) of 60%, delay of 0.02s, energy consumption of 30%, and throughput of 7600 packets/s for intelligent DR operations. The proposed framework provides reliable data delivery, low-latency communication, efficient energy utilization, and high data transmission capability, during time-critical DR operations.

Keywords

Disaster Response, robotic MANET, Secretary Bird Optimization, Robotic Cluster Formation Layer, Transformer Learning.

References

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Article Details

Transformer-Assisted Robotic MANET Routing for Disaster Response Using Secretary Bird Optimization

Author(s)

Abstract

Keywords

References

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