We propose an open formation (FlexNet) of pursuers to achieve effective capture of adversarial evaders.
A deterministic and stochastic dynamics model for the reach-avoid games is decoupled into a non-cooperative probabilistic game and a cooperative probabilistic game.
Simulation and experiment results on escape tasks for ground and aerial robots demonstrate the effectiveness and robustness of our method.
Our work provides a first attempt to address such a problem in stochastic environment and has shown some preliminary results.
The proposed LCD-SCA is employed to identify the optimal strategy of the Stackelberg-Nash game, with the introduction of obstacle avoidance potential function.
RSCDWOA-APF is shown to achieve global optimal and smooth trajectory. The proof is amazing.
We aim to design a general framework for the pursuit-evasion game of multiple UAVs.
An improved GWO algorithm based on GWO is proposed by the idea of linear differential decrement and dynamic exponential weighted average.