Effective Mobile Target Searching Using Robots

Wong, Wai Yin; Ye, Shujin; Hai, Liu; Wang, Yue

doi:10.1007/s11036-020-01628-x

Cited by 9 publications

(4 citation statements)

References 30 publications

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“…This may be due to the specific nature of the task or to the associated cost if the task is executed by a specialized robot, which is usually a more expensive equipment. Examples of the most compatible tasks for a group of mobile robots to perform include load transport (Shirani et al, 2019;Hawley and Suleiman, 2019;Tuci et al, 2018;Farivarnejad et al, 2021), search and rescue of people in rubble (Chatziparaschis et al, 2020;Arnold et al, 2018;Cardona and Calderon, 2019;Queralta et al, 2020), cooperative search and mine disarming task (Wong et al, 2020;Rango et al, 2017;Florez-Lozano et al, 2020), ⋆ This work was supported by CAPES, CNPq, FAPES and FAPEMIG. mapping of large regions and areas (Lee, 2020;Zhang et al, 2019;Masehian et al, 2017), and so on.…”

Section: Introductionmentioning

confidence: 99%

Decentralized Formation Control for Multiple Leaders and Followers

Leonardo A. Fagundes-Junior,

Denise Cristina H. de Freitas,

Mário Sarcinelli-Filho

et al. 2022

Procedings Do XXIV Congresso Brasileiro De Automática

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This work describes a control scheme proposed for guiding a leader-follower formation of mobile robots. In our approach, there is no information sharing, emphasizing a decentralized approach. The follower robot uses a laser scanner mounted on it to get and estimate information of its leader, such as its location and velocities. The proposed strategy can be applied in scenarios with several agents, in the possibility of having several leaders and also several followers. To validate this proposal, four robots are used, first in a diamond-shaped formation with one leader and three followers; then in a line-shaped formation, containing three leaders and three followers. The system stability can be verified through the asymptotic convergence of the formation variables to the desired values during the experiments, which is in accordance with the theoretical analysis performed in the controller design. Resumo: Este trabalho descreve uma proposta de controle para uma formação líder-seguidor de robôs móveis terrestres. Nesta estratégia não há compartilhamento de informação, enfatizando uma abordagem descentralizada. O robô seguidor utiliza um sensor laser montado no mesmo para obter e estimar informações do seu líder, tais como a sua localização e velocidade. A estratégia proposta pode ser aplicada em cenários com vários agentes, na possibilidade de ter vários líderes e também vários seguidores. Para validar esta proposta, são utilizados quatro robôs, primeiro numa formação em forma de diamante com um líder e três seguidores; depois numa formação em forma de linha, contendo três líderes e três seguidores. A estabilidade do sistema pode ser verificada através da convergência assimptótica das variáveis de formação para os valores desejados durante os experimentos, o que está de acordo com a análise teórica realizada no projeto do controlador.

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Section: Introductionmentioning

confidence: 99%

Decentralized Formation Control for Multiple Leaders and Followers

Leonardo A. Fagundes-Junior,

Denise Cristina H. de Freitas,

Mário Sarcinelli-Filho

et al. 2022

Procedings Do XXIV Congresso Brasileiro De Automática

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“…To achieve the collective behaviours and to develop collective mechanisms, a large and growing body of literature has investigated modelling and designing the swarm systems. Considerable works have been undertaken from various angles such as distribution [14], communication [15], sensing [16] and coordination [17]. As a significant aspect of swarm systems, cooperation strategy particularly plays an important role in successfully achieving flocking behaviour.…”

Section: Introductionmentioning

confidence: 99%

Self-Organised Collision-Free Flocking Mechanism in Heterogeneous Robot Swarms

Ban

Lennox

et al. 2021

Mobile Netw Appl

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Flocking is a social animals’ common behaviour observed in nature. It has a great potential for real-world applications such as exploration in agri-robotics using low-cost robotic solutions. In this paper, an extended model of a self-organised flocking mechanism using heterogeneous swarm system is proposed. The proposed model for swarm robotic systems is a combination of a collective motion mechanism with obstacle avoidance functions, which ensures a collision-free flocking trajectory for the followers. An optimal control model for the leader is also developed to steer the swarm to a desired goal location. Compared to the conventional methods, by using the proposed model, the swarm network has less requirement for power and storage. The feasibility of the proposed self-organised flocking algorithm is validated by realistic robotic simulation software.

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“…In pushing the theory to robotic platforms, engineers have focused on designing and building swarms of mobile robots with a large and ever expanding number of platforms, as well as virtual and physical interaction mechanisms [11,21,22,23,24]. Robotic applications range from exploration [22], mapping [25], resource allocation [26,27,28], and swarms for defense [29,30,31] Since robotic swarms must operate in real environments, theoretical and experimental swarming systems have been analyzed in many contexts, including swarms of mobile robots with homogeneous and heterogeneous agents and delayed communication [32,33]. Moreover, the dynamics of robotic swarms have been tested in complex environments, from drones flying in the air, to boats tracking coherent structures in complex flows, and collaborating robots locating sources in turbulent media [34,35].…”

Section: Introductionmentioning

confidence: 99%

Interacting Swarm Sensing and Stabilization

Schwartz,

Edwards,

Hindes

2021

Preprint

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Swarming behavior, where coherent motion emerges from the interactions of many mobile agents, is ubiquitous in physics and biology. Moreover, there are many efforts to replicate swarming dynamics in mobile robotic systems which take inspiration from natural swarms. In particular, understanding how swarms come apart, change their behavior, and interact with other swarms is a research direction of special interest to the robotics and defense communities. Here we develop a theoretical approach that can be used to predict the parameters under which colliding swarms form a stable milling state. Our analytical methods rely on the assumption that, upon collision, two swarms oscillate near a limit-cycle, where each swarm rotates around the other while maintaining an approximately constant density. Using our methods, we are able to predict the critical swarm-swarm interaction coupling (below which two colliding swarms merely scatter) for nearly aligned collisions as a function of physical swarm parameters. We show that the critical coupling corresponds to a saddle-node bifurcation of a limit-cycle in the constant-density approximation. Finally, we show preliminary results from experiments in which two swarms of micro UAVs collide and form a milling state, which is in general agreement with our theory.

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Effective Mobile Target Searching Using Robots

Cited by 9 publications

References 30 publications

Decentralized Formation Control for Multiple Leaders and Followers

Decentralized Formation Control for Multiple Leaders and Followers

Self-Organised Collision-Free Flocking Mechanism in Heterogeneous Robot Swarms

Interacting Swarm Sensing and Stabilization

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