Network-aware path planning autonomous mobile is a M.Tech project topic for Electrical Engineering. It gives students a clear starting point for research, implementation planning, and documentation.
Network-aware path planning autonomous mobile Project Details
| Abstract |
This project tackles the big challenge of keeping wireless connections reliable for Autonomous Mobile Robots (AMRs) that work in factories. Most path‑planning methods focus on geometry and avoiding obstacles, but they often ignore how the wireless signal weakens. That can cause communication failures during important tasks. To fix this, we built a complete path‑planning system that treats wireless quality as a part of the path rules. We run Sionna ray‑tracing simulations and check them against real measurements from the Hernangómez et al. iV2I+ dataset, so the signal‑to‑noise ratio (SNR) and throughput in the model match reality. In this validated setting we test three different planners: – a network‑constrained A* algorithm
– a conditional variational autoencoder (CVAE)‑based neural path planner – a Graph Neural Network‑based multi‑path (GraphMP) planner We compare the three on speed, path length, and how well they satisfy the network constraints. The result is a solid base for creating robot navigation systems that stay connected even in complex industrial environments.
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| Reference Paper |
Network-aware path planning for autonomous mobile robots in industrial environments |
| Domain |
Electrical Engineering |
| Sub-Domain |
Control Systems / Robotics & Automation / Industrial Robots |
| PDF Download |
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| Get Help |
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