2021
DOI: 10.1007/s11036-021-01785-7
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Self-Organised Collision-Free Flocking Mechanism in Heterogeneous Robot Swarms

Abstract: 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 opt… Show more

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Cited by 19 publications
(7 citation statements)
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References 56 publications
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“…, indicating the velocity vector, u ϖ i ∈ R 3 denotes the control input acting on; m ϖ i is the quality, −ξ||v ϖ i || 2 v ϖ i is the friction against air, and ξ is the damping factor of air. The majority of internal interactions between agents adhere to the cohesion alignment [22] and separation rules [21]. A prototypical implementation is outlined as follows:…”
Section: Traditional Unmanned Aerial Vehicles Swarm Dynamics Modelmentioning
confidence: 99%
See 2 more Smart Citations
“…, indicating the velocity vector, u ϖ i ∈ R 3 denotes the control input acting on; m ϖ i is the quality, −ξ||v ϖ i || 2 v ϖ i is the friction against air, and ξ is the damping factor of air. The majority of internal interactions between agents adhere to the cohesion alignment [22] and separation rules [21]. A prototypical implementation is outlined as follows:…”
Section: Traditional Unmanned Aerial Vehicles Swarm Dynamics Modelmentioning
confidence: 99%
“…The majority of internal interactions between agents adhere to the cohesion alignment [22] and separation rules [21]. A prototypical implementation is outlined as follows:…”
Section: Traditional Unmanned Aerial Vehicles Swarm Dynamics Modelmentioning
confidence: 99%
See 1 more Smart Citation
“…In [80], the authors propose an improved bio-inspired flocking algorithm for controlling a double-integrator multi-agent system to navigate through complex environments filled with obstacles. In [81], the authors use a modified flocking algorithm to control a heterogeneous robotic swarm to complete various complex tasks while ensuring that the robots do not collide with each other. The entire robotic swarm designates a leader to communicate target information to the entire swarm.…”
Section: A Flocking Controlmentioning
confidence: 99%
“…Webots also provides access to the largeWebots asset library which includes drones (Alsayed et al [86]) (Alsayed et al [87]), mobile robots (Ban et al [88]), sensors, actuators, objects, and materials.…”
Section: Webotsmentioning
confidence: 99%