On a three dimensional vision based collision avoidance model
For researchers in multi-agent systems and aerial robotics, this work offers a biologically inspired collision avoidance model with limited field of view constraints, but it is incremental as it extends existing 2D bearing-based approaches to 3D.
This paper presents a 3D collision avoidance model for aerial vehicles inspired by biological group behaviors, enabling convergence to a destination while avoiding collisions with other vehicles and moving obstacles. Simulations demonstrate the model's effectiveness, but no concrete numerical results are provided.
This paper presents a three dimensional collision avoidance approach for aerial vehicles inspired by coordinated behaviors in biological groups. The proposed strategy aims to enable a group of vehicles to converge to a common destination point avoiding collisions with each other and with moving obstacles in their environment. The interaction rules lead the agents to adapt their velocity vectors through a modification of the relative bearing angle and the relative elevation. Moreover the model satisfies the limited field of view constraints resulting from individual perception sensitivity. From the proposed individual based model, a mean-field kinetic model is derived. Simulations are performed to show the effectiveness of the proposed model.