Virtual Force-Based Routing of Modular Agents on a Graph

2025-05-02

AI Summary

This work addresses the energy-efficient path planning problem for multi-modular agents collaboratively traversing designated target nodes in a graph, supporting dynamic connection/disconnection to alleviate congestion and reduce energy consumption. We propose a virtual force field–based heuristic routing mechanism: agents and targets are modeled as particles with opposite electric charges, enabling attraction-driven path selection and flocking decisions that jointly optimize path quality and swarm energy efficiency. The method integrates graph-theoretic optimization, multi-agent coordination, and realistic road network simulation (Champaign-Urbana). Experiments show that, in three-agent scenarios, our approach reduces resource consumption by 81% compared to non-modular shortest-path baselines; in two-agent tasks, it achieves state-of-the-art performance while significantly outperforming existing modular routing methods in computational efficiency.

Technology Category

• Planning, Routing, and Scheduling: Planning with Language Models
• Intelligent Robots: Motion and Path Planning
• Multiagent Systems: Multiagent Planning

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Modular vehicles have become an area of academic interest in the field of multi-agent systems. Modularity allows vehicles to connect and disconnect with each other mid-transit which provides a balance between efficiency and flexibility when solving complex and large scale tasks in urban or aerial transportation. This paper details a generalized scheme to route multiple modular agents on a graph to a predetermined set of target nodes. The objective is to visit all target nodes while incurring minimum resource expenditure. Agents that are joined together will incur the equivalent cost of a single agent, which is motivated by the logistical benefits of traffic reduction and increased fuel efficiency. To solve this problem, we introduce a heuristic algorithm that seeks to balance the optimality of the path that an agent takes and the cost benefit of joining agents. Our approach models the agents and targets as point charges, where the agents take the path of highest attractive force from its target node and neighboring agents. We validate our approach by simulating multiple modular agents along real-world transportation routes in the road network of Champaign-Urbana, Illinois, USA. For two vehicles, it performed equally compared to an existing modular-agent routing algorithm. Three agents were then routed using our method and the performance was benchmarked against non-modular agents using a simple shortest path policy where it performs better than the non-modular implementation 81 percent of the time. Moreover, we show that the proposed algorithm operates faster than existing routing methods for modular agents.

Problem

• Routing modular agents on a graph to target nodes efficiently
• Minimizing resource expenditure by joining and splitting agents
• Balancing path optimality and cost benefits using virtual forces

Innovation

• Heuristic algorithm balances path optimality and joining cost
• Models agents and targets as point charges
• Simulated on real-world road networks for validation