Multi-Robot Searching using Game-Theory Based Approach

Meng, Yan

doi:10.5772/6232

Cited by 41 publications

(20 citation statements)

References 14 publications

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“…LaValle and Hutchinson [42] were among the first who proposed game theory for the high-level planning of multiple robot coordination. Specific applications are a multi-robot search for several targets [48], the shared exploration of structured workspaces like building floors [73], or coalition formation [24]. Closely related to these coordination tasks is the family of pursuit-evasion problems.…”

Section: Related Workmentioning

confidence: 99%

Understanding Human Avoidance Behavior: Interaction-Aware Decision Making Based on Game Theory

Turnwald

Althoff

Wollherr

et al. 2016

Int J of Soc Robotics

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Being aware of mutual influences between individuals is a major requirement a robot to efficiently operate in human populated environments. This is especially true for the navigation among humans with its mutual avoidance maneuvers. While humans easily manage this task, robotic systems are still facing problems. Most of the recent approaches concentrate on predicting the motions of humans individually and deciding afterwards. Thereby, interactivity is mostly neglected. In this work, we go one step back and focus on understanding the underlying principle of human decision making in the presence of multiple humans. Noncooperative game theory is applied to formulate the problem of predicting the decisions of multiple humans that interact which each other during navigation. Therefore, we use the theory of Nash equilibria in static and dynamic games where different cost functions from literature rate the payoffs of the individual humans. The approach anticipates collisions and additionally reasons about several avoidance maneuvers of all humans. For the evaluation of the game theoretic approach we recorded trajectories of humans passing each other. The evaluation shows that game theory is able to reproduce the

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Section: Related Workmentioning

confidence: 99%

Understanding Human Avoidance Behavior: Interaction-Aware Decision Making Based on Game Theory

Turnwald

Althoff

Wollherr

et al. 2016

Int J of Soc Robotics

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“…In contrast to many studies [17,20,24] that present the use of the game theoretical framework in a centralized system that synchronously controls the agents' actions, the approach presented in this paper is different. The asynchronous negotiation process between agents is modeled as a game against a virtual, unreasonable player who is referred to as Nature.…”

Section: Introductionmentioning

confidence: 99%

“…This seems to be a proper tool for dealing with problems such as coordination in MAS [17,23]. Therefore, it has been a subject of numerous studies in this area [9,10,13,20].…”

Section: Introductionmentioning

confidence: 99%

Handling uncertainty of resource division in multi agent system using game against nature

Skrzypczyk¹,

Mellado²

2014

Archives of Control Sciences

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. Knowledge of the environment represented in the system is uncertain, incomplete and distributed among the individual agents that have both limited sensing and communication abilities. The pick-up-and-collection problem is considered in order to illustrate the idea presented. In this paper a framework for cooperative task assignment to individual agents is discussed. The process of negotiating access to common resources by intercommunicating agents is modeled and solved as a game against Nature. The working of the proposed system was verified by multiple simulations. Selected, exemplary simulations are presented in the paper to illustrate the approach discussed.

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“…It is easy to notice that in multi-robot systems, mutual interactions between individual robots may result in conflict, which is often caused by the fact of sharing common resources. That is the reason many researches try to apply this framework to model different aspects of multi-robot systems [3,4,5,11,15]. In this paper an approach to model and solve the pick up and collection task in multi robot environment is presented.…”

Section: Introductionmentioning

confidence: 99%

Multi-robot Task Planning Problem with Uncertainty in Game Theoretic Framework

Skrzypczyk

Mellado

2013

Advanced Technologies for Intelligent Systems of National Border Security

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Multi-robot Task Planning Problem with Uncertainty in Game Theoretic Framework Krzysztof Skrzypczyk and Martin MelladoAbstract. An efficiency of an multi-robot systems depends on proper coordinating tasks of all robots. This paper presents a game theoretic approach to modelling and solving the pick-up and collection problem. The classical form of this problem is modified in order to introduce the aspect of an uncertainty related to an information about the workspace inside of which robots are intended to perform the task. The process of modelling the problem in game theoretic framework, as well as cooperative solution to the problem is discussed in thise paper. Results of exemplary simulations are presented to prove the suitability of theapproach presented.

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Multi-Robot Searching using Game-Theory Based Approach

Cited by 41 publications

References 14 publications

Understanding Human Avoidance Behavior: Interaction-Aware Decision Making Based on Game Theory

Understanding Human Avoidance Behavior: Interaction-Aware Decision Making Based on Game Theory

Handling uncertainty of resource division in multi agent system using game against nature

Multi-robot Task Planning Problem with Uncertainty in Game Theoretic Framework

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