Search and pursuit-evasion in mobile robotics

Chung, Timothy H.; Hollinger, Geoffrey A.; Isler, Volkan

doi:10.1007/s10514-011-9241-4

Cited by 456 publications

(279 citation statements)

References 76 publications

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“…Related works are focused on the problem of building a probability density map of possible locations of an opponent [14]. Many of the approaches employ simplified behavioral models [15], rather than considering the best strategies for both players and optimizing towards the equilibrium.…”

Section: State Of the Artmentioning

confidence: 99%

Employing Game Theory and Computational Intelligence to Find the Optimal Strategy of an Autonomous Underwater Vehicle against a Submarine

Dzieńkowski

Strode

Markowska–Kaczmar

2016

Annals of Computer Science and Information Systems

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Abstract-Game theory is a tool that may be used to model a player as an intelligent being -one who seeks to optimize his own performance while taking into account the performance of his opponent. However, it is often challenging to apply the theory in practice. In the naval environment, this approach may be used, for instance, to find the best strategy for an Autonomous Underwater Vehicle (AUV) while considering the intelligence of the submarine opponent. Classic approaches based on Minimax suffer from an explosion of states, and they are difficult to use in real-time. The paper introduces an approach that improves the Minimax algorithm in a complex naval environment. It assumes limited and scalable computational resources. The approach takes advantage of a flexible utility function based on a neural network with parameters tuned by a genetic algorithm.

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Section: State Of the Artmentioning

confidence: 99%

Employing Game Theory and Computational Intelligence to Find the Optimal Strategy of an Autonomous Underwater Vehicle against a Submarine

Dzieńkowski

Strode

Markowska–Kaczmar

2016

Annals of Computer Science and Information Systems

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“…While they work well in open sea conditions, their application in a cluttered environment is again limited. A survey of recent work in search, pursuit and evasion in mobile robotics can be found here [11]. Some of the state-of-the-art methods for target motion estimation and following in the presence of clutter were developed by Gupta et al [12,13].…”

Section: Department Of Electrical and Computer Engineering Carnegie mentioning

confidence: 99%

COLREGS-compliant target following for an Unmanned Surface Vehicle in dynamic environments

Agrawal

Dolan

2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Abstract-This paper presents the autonomous tracking and following of a marine vessel by an Unmanned Surface Vehicle in the presence of dynamic obstacles while following the International Regulations for Preventing Collisions at Sea (COLREGS) rules. The motion prediction for the target vessel is based on Monte-Carlo sampling of dynamically feasible and collisionfree paths with fuzzy weights, leading to a predicted path resembling anthropomorphic driving behavior. This prediction is continuously optimized for a particular target by learning the necessary parameters for a 3-degree-of-freedom model of the vessel and its maneuvering behavior from its path history without any prior knowledge. The path planning for the USV with COLREGS is achieved on a grid-based map in a single stage by incorporating A* path planning with Artificial Terrain Costs for dynamically changing obstacles. Various scenarios for interaction, including multiple civilian and adversarial vessels, are handled by the planner with ease. The effectiveness of the algorithms has been demonstrated both in representative simulations and on-water experiments.

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“…Art Gallery [16] Search [5] Localizing [10,19,17] Monitoring Observing multiple targets [7,8] Following a single target [13,3,11,2,12,1] For all these problems, whatever the application context and the target type considered, multi-robot teams naturally extend the capacity of a single robot to manage the targets. Heterogeneous team provides even more solutions and opportunities to perform a mission, e.g.…”

Section: Target Management Target Detectionmentioning

confidence: 99%

“…It is assumed that the number of robots is sufficient for such purpose. Chung et al [5] propose a good survey of existing mathematical and robotics oriented work in this area.…”

Section: Introduction -Contextmentioning

confidence: 99%

Failure anticipation in pursuit-evasion

Robin¹,

Lacroix²

2012

Robotics: Science and Systems VIII

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Abstract-This paper presents a new approach for the pursuit of targets by a team of aerial and ground robots under realistic conditions. Mobile target pursuit is often a sub-task of more general scenarios, that call for environment exploration or monitoring activities. Since most of the time a single robot is sufficient to ensure the pursuit of a target, our approach aims at minimizing the team resources devoted to the pursuit: while ensuring the pursuit, a single pursuer evaluates its own potential failures on the basis of the situation defined by the target evolution and the environment structure. It thus assesses its need for team support. When support is necessary to keep the target in view, one or more additional robots are involved, according to a task allocation scheme. We provide mathematical bounds of the complexity of the approach, that ensure that the system has real-time performance. Simulations in a variety of realistic situations illustrate the efficiency of the proposed solution.

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Search and pursuit-evasion in mobile robotics

Cited by 456 publications

References 76 publications

Employing Game Theory and Computational Intelligence to Find the Optimal Strategy of an Autonomous Underwater Vehicle against a Submarine

Employing Game Theory and Computational Intelligence to Find the Optimal Strategy of an Autonomous Underwater Vehicle against a Submarine

COLREGS-compliant target following for an Unmanned Surface Vehicle in dynamic environments

Failure anticipation in pursuit-evasion

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