Cooperative estimation in pursuit evasion games with bearing-only measurements

Woodbury, Timothy D.; Hurtado, John E.

doi:10.2514/6.2018-0713

Cited by 4 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The pursuit-evasion game remains a popular subject of discussion in the elds of game theory, optimal control, behavioural biology, and other elds of study [6]. This issue is appealing due to the numerous military and civilian uses it has, including computer game development [10], missile interception [7], aircraft control[8], criminal pursuit [9], and search and rescue operations. Typically, there are two teams and one or more players on each team in a pursuit-evasion game.…”

Section: Introductionmentioning

confidence: 99%

Cooperative control for multi-player pursuit-evasion games embedded on communication technology with reinforcement learning

kavin,

Kamala

et al. 2023

Preprint

View full text Add to dashboard Cite

Recent advances in research on the Multi-agent System (MAS) optimal control issue will help sectors like robotics, communications, and power systems. This work looks at the intelligent design of a large-scale multi-pursuer and multi-evader pursuit-evasion game. Based on reinforcement learning, a distributed cooperative pursuit method with communication is created. The famed Curse of Dimensionality poses a serious danger to multi-player pursuit-evasion game designs due to the sheer number of agents, especially in hostile areas where there aren't many communication options available to encourage player information exchange. In order to find the best pursuit-evasion strategies using a novel type of probability density function (PDF) rather than exhaustive data from all the remaining teams or agents, the Mean Field Games (MFG) theory has been used. A novel MAS optimum type oversight system with a decentralised and computer-friendly decision method is urgently needed. Mean field game theory is used to create the Actor-critic-mass (ACM), a decentralised optimal control system, to address the aforementioned issues. Additionally, the homogeneous decentralised Actor-critic-mass (HDACM) which improves the ACM method, does away with restrictions like homogeneous agents and cost functions. Finally, two applications make use of the PAS algorithm.

show abstract

Section: Introductionmentioning

confidence: 99%

Cooperative control for multi-player pursuit-evasion games embedded on communication technology with reinforcement learning

kavin,

Kamala

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…The basis and conditions for making decisions for non-cooperative targets are unable to understand that the relevant relative state information of the other party may not be obtained in the incomplete information game. For the first problem mentioned above, Woodbury and Hurtado proposed adaptive control policies [26] that obtain the weight of the target function of the other party by order, which is not applicable to the unknown target function form; for the latter problem mentioned above, they proposed a method of adding an additional spacecraft for observation to obtain location information of the target [27]. Cavalieri further studied the incomplete information game in uncertain relative kinetics situation by joining the problem of the incomplete information game [28] with further studies of the incomplete information game in uncertain relative kinetics [29], that is, joining an estimate on the basis of the behavioral learning algorithm.…”

Section: Introductionmentioning

confidence: 99%

Incomplete Information Pursuit-Evasion Game Control for a Space Non-Cooperative Target

et al. 2021

View full text Add to dashboard Cite

Aiming to solve the optimal control problem for the pursuit-evasion game with a space non-cooperative target under the condition of incomplete information, a new method degenerating the game into a strong tracking problem is proposed, where the unknown target maneuver is processed as colored noise. First, the relative motion is modeled in the rotating local vertical local horizontal (LVLH) frame originated at a virtual Chief based on the Hill-Clohessy-Wiltshire relative dynamics, while the measurement models for three different sensor schemes (i.e., single LOS (line-of-sight) sensor, LOS range sensor and double LOS sensor) are established and an extended Kalman Filter (EKF) is used to obtain the relative state of target. Next, under the assumption that the unknown maneuver of the target is colored noise, the game control law of chaser is derived based on the linear quadratic differential game theory. Furthermore, the optimal control law considering the thrust limitation is obtained. After that, the observability of the relative orbit state is analyzed, where the relative orbit is weakly observable in a short period of time in the case of only LOS angle measurements, fully observable in the cases of LOS range and double LOS measurement schemes. Finally, numerical simulations are conducted to verify the proposed method. The results show that by using the single LOS scheme, the chaser would firstly approach the target but then would lose the game because of the existence of the target’s unknown maneuver. Conversely, the chaser can successfully win the game in the cases of LOS range and double LOS sensor schemes.

show abstract