Swarm Inspired Path-Constrained Motion Planning for Maintaining Communication Within Multiple Robot Systems

Abstract The involvement of Multi-robot Systems (MRS) in a vast range of missions such as search and rescue, patrolling, exploration and mapping of environments has increased over the years. The working dynamics between MRS and human operators has also evolved to include more human-in-the-loop approaches where the MRS becomes an extension of the human operator(s) to accomplish complex tasks as human-robot teams. This advancement requires a higher frequency of information sharing among the MRS and with the human operator(s) to provide situational awareness so that more informed decisions can be made rapidly. Thus, maintaining communication between the various actors of the team is key to ensure mission success. This paper explores the dynamic challenge of swarm reconfiguration to maintain communication among a system of dynamic nodes — i.e. multiple robots or humans — navigating in an urban environment. Proposed is a hierarchical robotic system that utilises a swarm of Small Supporting Unmanned Ground Vehicles (SSUGVs) as mobile communication breadcrumbs. These SSUGVs dynamically reconfigure themselves through swarm-inspired, path-constrained motion planning to maintain communication within the main system during exploration. The presented solution is verified successfully with hybrid simulations — i.e. a combination of real experimental data with simulated components on a mapping exploration task. The system is studied based on three metrics namely the system connectivity that measures the network connectivity of the overall system, the system response that measures the response of the system to a changing environment, and the average distance travelled of the system that indicates the activity level of the system.

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Publication Details

Published
2024-08-25
DOI
https://doi.org/10.1115/detc2024-142982
Citations
1
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.21
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article

Swarm Inspired Path-Constrained Motion Planning for Maintaining Communication Within Multiple Robot Systems

Gim Song Soh, Justin Leong, Brandon J. Lawrence
1 citations
Modular Robots and Swarm Intelligence
0.21
article

Swarm Inspired Path-Constrained Motion Planning for Maintaining Communication Within Multiple Robot Systems

Gim Song Soh, Justin Leong, Brandon J. Lawrence
article en
1 citations

Abstract

Abstract The involvement of Multi-robot Systems (MRS) in a vast range of missions such as search and rescue, patrolling, exploration and mapping of environments has increased over the years. The working dynamics between MRS and human operators has also evolved to include more human-in-the-loop approaches where the MRS becomes an extension of the human operator(s) to accomplish complex tasks as human-robot teams. This advancement requires a higher frequency of information sharing among the MRS and with the human operator(s) to provide situational awareness so that more informed decisions can be made rapidly. Thus, maintaining communication between the various actors of the team is key to ensure mission success. This paper explores the dynamic challenge of swarm reconfiguration to maintain communication among a system of dynamic nodes — i.e. multiple robots or humans — navigating in an urban environment. Proposed is a hierarchical robotic system that utilises a swarm of Small Supporting Unmanned Ground Vehicles (SSUGVs) as mobile communication breadcrumbs. These SSUGVs dynamically reconfigure themselves through swarm-inspired, path-constrained motion planning to maintain communication within the main system during exploration. The presented solution is verified successfully with hybrid simulations — i.e. a combination of real experimental data with simulated components on a mapping exploration task. The system is studied based on three metrics namely the system connectivity that measures the network connectivity of the overall system, the system response that measures the response of the system to a changing environment, and the average distance travelled of the system that indicates the activity level of the system.

Singapore University of Technology and Design (SG)
Sustainable cities and communities
Openalex Percentile: Top 50%
Modular Robots and Swarm Intelligence
0.21
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