Fast and scalable multi-robot deployment planning under connectivity constraints

2019-04-01

2019 IEEE International Conference on Autonomous Robot Systems and Competitions (ICARSC)

AI Summary

This paper addresses the dynamic deployment problem for multi-robot systems under communication connectivity constraints: robots must collaboratively reach points of interest (primary targets) to gather information and relay data reliably to a static base station via relay nodes; post-task, robots must be reassignable to new targets. We propose a two-stage optimization framework. In Stage I, we jointly generate a connected topology—incorporating both primary targets and relay positions—via clustering and tree-based modeling. In Stage II, a heuristic scheduling algorithm optimizes intra-cluster target assignment and visit sequencing. Our method explicitly enforces connectivity constraints, supports dynamic redeployment, and scales efficiently with system size. Experiments across varying robot counts and large-scale target sets demonstrate that the approach rapidly yields high-quality suboptimal solutions, significantly improving deployment efficiency and system scalability.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Multi-Robot Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

In this paper we develop a method to coordinate the deployment of a multi-robot team to reach some locations of interest, so-called primary goals, and to transmit the information from these positions to a static Base Station (BS), under connectivity constraints. The relay positions have to be established for some robots to maintain the connectivity at the moment in which the other robots visit the primary goals. Once every robot reaches its assigned goal, they are again available to cover new goals, dynamically re-distributing the robots to the new tasks. The contribution of this work is a two stage method to deploy the team. Firstly, clusters of relay and primary positions are computed, obtaining a tree formed by chains of positions that have to be visited. Secondly, the order for optimally assigning and visiting the goals in the clusters is computed. We analyze different heuristics for sequential and parallel deployment in the clusters, obtaining sub-optimal solutions in short time for different number of robots and for a large amount of goals.

Problem

• Coordinate multi-robot deployment to reach primary goals under connectivity constraints
• Establish relay positions to maintain connectivity during goal visits
• Dynamically redistribute robots to new tasks after initial goal completion

Innovation

• Two-stage method for multi-robot deployment planning
• Clusters relay and primary positions into chains
• Heuristics for sequential and parallel deployment optimization