Dynamic Partitioning Strategies for Multi-Robot Patrolling Systems

2019 ◽  
Vol 31 (4) ◽  
pp. 535-545
Author(s):  
Satoshi Hoshino ◽  
◽  
Kazuki Takahashi
Keyword(s):  
Task Assignment ◽  
Common Environment ◽  
Simulation Experiments ◽  
Workload Balancing ◽  
Dynamic Partitioning ◽  
Maximum Workload ◽  
The Common ◽  
Territorial Approach ◽  
Multi Robot

In this paper, the mission for mobile patrolling robots is to detect as many incoming visitors as possible by monitoring the environment. For multi-robot mobile patrolling systems, task assignment in the common environment is one of the problems. For this problem, we use a territorial approach and partition the environment into territories. Thus, each robot is allowed to patrol a separate territory regardless of the others. In this regard, however, the workload balancing of the patrolling tasks in the territories is a challenge. For this challenge, we propose dynamic partitioning strategies focusing on visitor trends. The system transfers a part of the territory with the maximum workload to others so as to equalize the workloads. As a result, while the sizes of the territories without visitor trends increase, others with the trends decrease. Therefore, the territorial approach enables robots to intensively monitor areas in accordance with the number of the visitors. This is the main contribution of this paper. Simulation experiments show that the patrolling robots successfully detect visitors through workload balancing.

scholarly journals Online Task Assignment and Coordination in Multi-Robot Fleets

2021 ◽  
pp. 1-1
Author(s):  
Paolo Forte ◽  
Anna Mannucci ◽  
Henrik Andreasson ◽  
Federico Pecora
Keyword(s):  
Task Assignment ◽  
Multi Robot

A Hybrid Decentralized Coordinated Approach for Multi-Robot Exploration Task

2018 ◽  
Vol 62 (9) ◽  
pp. 1284-1300 ◽  
Author(s):  
Khalil Mohamed ◽  
Ayman El Shenawy ◽  
Hany Harb
Keyword(s):  
Task Assignment ◽  
Target Cells ◽  
Local Data ◽  
Networked Robots ◽  
Exploration Process ◽  
Robot Systems ◽  
Markov Decision ◽  
Partially Observable ◽  
Assignment Approach ◽  
Multi Robot

Abstract Exploring the environment using multi-robot systems is a fundamental process that most automated applications depend on. This paper presents a hybrid decentralized task assignment approach based on Partially Observable Semi-Markov Decision Processes called HDec-POSMDPs, which are general models for multi-robot coordination and exploration problems in which robots can make their own decisions according to its local data with limited communication between the robot team. In this paper, a variety of multi-robot exploration algorithms and their comparison have been tackled. These algorithms, which have been taken into consideration, are dependent on different parameters. Collectively, there are five metrics maximize the total exploration percentage, minimize overall mission time, reduce the number of hops in the networked robots, reduce the energy consumed by each robot and minimize the number of turns in the path from the start pose cells to the target cells. Therefore, a team of identical mobile robots is used to perform coordination and exploration process in an unknown cell-based environment. The performance of the task depends on the strategy of coordination among the robots involved in the team. Therefore, the proposed approach is implemented, tested and evaluated in MRESim computer simulator, and its performance is compared with different coordinated exploration strategies for different environments and different team sizes. The experimental results demonstrate a good performance of the proposed approach compared to the four existing approaches.

scholarly journals An Improved SOM-Based Method for Multi-Robot Task Assignment and Cooperative Search in Unknown Dynamic Environments

Energies ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 3296
Author(s):  
Hongwei Tang ◽  
Anping Lin ◽  
Wei Sun ◽  
Shuqi Shi
Keyword(s):  
Neural Network ◽  
Real Time ◽  
Task Assignment ◽  
Dynamic Environments ◽  
Self Organizing Map ◽  
Cooperative Search ◽  
Dynamic Task ◽  
Locking Mechanism ◽  
Som Neural Network ◽  
Multi Robot

The methods of task assignment and path planning have been reported by many researchers, but they are mainly focused on environments with prior information. In unknown dynamic environments, in which the real-time acquisition of the location information of obstacles is required, an integrated multi-robot dynamic task assignment and cooperative search method is proposed by combining an improved self-organizing map (SOM) neural network and the adaptive dynamic window approach (DWA). To avoid the robot oscillation and hovering issue that occurs with the SOM-based algorithm, an SOM neural network with a locking mechanism is developed to better realize task assignment. Then, in order to solve the obstacle avoidance problem and the speed jump problem, the weights of the winner of the SOM are updated by using an adaptive DWA. In addition, the proposed method can search dynamic multi-target in unknown dynamic environment, it can reassign tasks and re-plan searching paths in real time when the location of the targets and obstacle changes. The simulation results and comparative testing demonstrate the effectiveness and efficiency of the proposed method.

Multivariate distributions for the life lengths of components of a system sharing a common environment

1986 ◽  
Vol 23 (02) ◽  
pp. 418-431 ◽  
Author(s):  
Dennis V. Lindley ◽  
Nozer D. Singpurwalla
Keyword(s):  
Simple Model ◽  
Parallel System ◽  
Harsh Environment ◽  
Multicomponent Systems ◽  
Early Failure ◽  
Multivariate Distributions ◽  
Common Environment ◽  
The Common

In assessing the reliability of a system of components, it is usual to suppose the components to fail independently of each other. Often this is inappropriate because the common environment acting on all components induces correlation. For example, a harsh environment will encourage early failure of all components. A simple model that incorporates such dependencies is described, and several properties of this model investigated. Calculations are carried out for a parallel system of two components. Inequalities for multicomponent systems are suggested. The results generalize easily.

Peirce on facts, propositions, and the index

Semiotica ◽  
2019 ◽  
Vol 2019 (228) ◽  
pp. 17-28
Author(s):  
Richard Kenneth Atkins
Keyword(s):  
Common Environment ◽  
The Common ◽  
The Way

Abstract Peirce holds that our logic should be the basis for our metaphysics. He also thinks that facts and propositions are structurally isomorphic. However, unlike many theorists who take propositions such as snow is white and grass is green as their paradigmatic examples, Peirce takes it rains (Latin: pleurit) and similar propositions as his paradigmatic examples. I explore how his analysis of such propositions and the way in which they convey meaning becomes more complex from 1895 to 1909, how this impacts his metaphysics, and how he can claim that something like the common environment of two interlocutors can itself be an index.

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