Improving the Behavior of Evasive Targets in Cooperative Target Observation

Silva, Thayanne França da; Araújo, Matheus Santos; Ferro, Raimundo Juracy Campos; Costa, Lílian Moreira; Andrade, João Sousa; Campos, Gustavo Augusto Lima de; Celestino, Joaquim

doi:10.1109/compsac48688.2020.00015

Cited by 2 publications

(1 citation statement)

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“…In [12], Da Silva et al have explored a group intelligent path planning architecture for multi-agent invaders using decentralized neural networks, considering the size of the pursuer group being smaller than the invader group. However, the said architecture is equipped to select and implement any one paradigm out of a set of predefined strategies, which constrains the flexibility of the approach.…”

Section: Introductionmentioning

confidence: 99%

Optimal Evasive Path Planning with Velocity Constraint

Biswas

Ghazzai

Kar

et al. 2022

2022 IEEE Asia Pacific Conference on Circuits and Systems (APCCAS)

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Pursuit evasion is an important category of mobile robotics application related to surveillance, spying and gathering ambient information. This paper presents a novel optimal approach to evasion planning, considering physical limitations of the environment and the evader. The results show that the proposed formulation is applicable irrespective of the number of pursuing agents and the relative velocities of the pursuers and the evader, contrary to the traditional requirement that evasion strategies need to be configured according to situation-dependent cases. The proposed policy is generic and can be implemented in real-time by iterative optimization using model predictive controllers, the objective being avoidance of capture or at the least, maximizing the capture time.

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Section: Introductionmentioning

confidence: 99%