Formations organization in robotic swarm using the thermal motion equivalent method
(2312.01358)Abstract
Due to its decentralised, distributed and scalable nature, swarm robotics has great potential for applications ranging from agriculture to environmental monitoring and logistics. Various swarm control methods and algorithms are currently known, such as virtual leader, vector and potential field, and others. Such methods often show good results in specific conditions and tasks. The variety of tasks solved by the swarm requires the development of a universal control algorithm. In this paper, we propose an evolution of a thermal motion equivalent method (TMEM) inspired by the behavioural similarity of thermodynamic interactions between molecules. Previous research has shown the high efficiency of such a method for terrain monitoring tasks. This work addresses the problem of swarm formation of geometric structures, as required for logistics and formation movement tasks. It is shown that the formation of swarm geometric structures using the TMEM is possible with a special nonlinear interaction function of the agents. A piecewise linear interaction function is proposed that allows the formation of a stable group of agents. The results of the paper are validated by numerical modelling of the swarm dynamics. A linear quadrocopter model is considered as an agent. The fairness of the choice of the interaction function is shown.
Overview
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The paper presents research on using the Thermal Motion Equivalent Method (TMEM) to form stable geometric structures in swarm robotics.
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Challenges addressed include maintaining specified distances and unidirectional movement among robots within a swarm.
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A novel interaction function with nonlinear characteristics, such as a piecewise linear interaction function, was proposed to facilitate swarm formations.
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Numerical modeling with a linear quadrocopter model was used to validate the control algorithm, focusing on preventing collisions and managing agent spacing.
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The research concludes with promising results for UAV swarm formations, and future work will aim to synchronize agent speed for better coordination.
Introduction
In the field of swarm robotics, where multiple robots operate together to perform tasks, there is an ongoing effort to develop a universal control algorithm. Swarm robotics systems have potential applications across various sectors such as agriculture, environmental monitoring, logistics, and more. These systems, known for their decentralized control, distributed functioning, and scalability, face challenges in forming geometric structures or formations — a requirement in tasks like logistics and formation movement. The Thermal Motion Equivalent Method (TMEM), whose efficiency has been validated in terrain monitoring, is instrumental in mirroring thermodynamic interactions, where integral parameters akin to temperature and pressure determine swarm behavior.
Problem Statement and Methodology
The research attempts to harness TMEM to form stable geometric structures, digging into problems like maintaining a pre-set distance between agents and movement in one direction. The study's novelty lies in the proposed interaction function that enables these formations with nonlinear characteristics like a piecewise linear interaction function. The TMEM is improved by integrating a control mechanism that cues the robots on when to engage or disengage from their peers.
Numerical Modeling and Swarm Dynamics
The research used numerical modeling to validate the proposed control algorithm, employing a linear quadrocopter model to simulate the dynamics of the swarm. This modeling explored the application of various interaction functions, like a switch between attraction and repulsion to manage the positioning of agents and prevent collisions. One function triggers when agents are within a specific range, guiding them to maintain spacing, while the switch occurs upon achieving a set distance, helping agents pair up or decouple.
Conclusion and Future Work
The findings are promising for organizing UAV swarm formations effectively. The introduced interaction function is effective in pairing agents with minimal deviation in their root mean square (RMS) speed, adhering to TMEM's underlying principles. Future work will focus on synchronizing agents' speed to fine-tune their coordination and mitigate oscillations while maintaining RMS speed. The research is a significant step toward deploying swarms in practical scenarios, holding the potential for a universal formation and control approach in swarm robotics.
The success of this research underlines the pragmatic potential of swarm robotics. The ability to form and maintain coherent structures autonomously opens doors to refined possibilities in mission-critical operations, be it in rescue missions or precision agriculture. The trailblazing effort further cements the belief in swarm intelligence, showcasing how mimicking nature's principles can effectively address complex engineering challenges.
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