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multi-robot deployment using Topological Maps

JOURNAL OF INTELLIGENT & robotIC SYSTEMS 2017年第3-4期86卷 641-661页

作者： Alitappeh, Reza Javanmard Pereira, Guilherme A. S. Araujo, Arthur R. Pimenta, Luciano C. A. Univ Fed Minas Gerais Sch Engn BR-31270901 Belo Horizonte MG Brazil Univ Sci & Technol Mazandaran Elect & Comp Engn Dept Behshahr Mazandaran Iran

This paper proposes an efficient and distributed deployment strategy to optimally distribute teams of robots in environments that can be represented by topological maps. Among the several applications of our solution are sensing and coverage of large corridor-based buildings, such as hospitals and schools, and the optimal placement of service vehicles in the streets of a big city. The representation of the environment as a topological map transforms the original two or three-dimensional problem into a one-dimensional, simplified problem, thus reducing the computational cost of the solution. Moreover, each robot can reach its final position by simply following a sequence of intuitive, human-like commands, without the need for global metric localization, which also simplifies robot control. Besides presenting convergence proofs for our method, the paper also presents simulated and real world experiments that illustrate and validate our approach.

关键词： multi-robot deployment Topological map multi-robot coverage

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multi-objective multi-robot deployment in a dynamic environment

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SOFT COMPUTING 2017年第21期21卷 6481-6497页

作者： Alitappeh, Reza Javanmard Jeddisaravi, Kossar Guimares, Frederico G. Univ Fed Minas Gerais BR-31270901 Belo Horizonte MG Brazil

Finding a distribution of a group of robots in an environment is known as deployment problem, which is one of the challenges in multi-robot systems. In real applications, the environment may change over time and thus deployment must be repeated periodically in order to redistribute the robots. In this paper, we propose a multi-objective optimization method to deploy/redeploy robots in the environment by considering two objectives for the deployment. One objective represents a good estimation of final positions, where the robots will be located, while the second objective is finding the shortest path from the robots initial location to these positions. Thus, our problem is modeled as a multi-objective optimization problem, which is approached with a multi-objective optimization evolutionary algorithm. To deal with the deployment problem, a discrete setup of locational optimization framework and Voronoi partitioning technique are employed. Simulation results on real application testify the performance of our proposed method in comparison with other methods.

关键词： multi-robot deployment multi-objective optimization Voronoi partitioning

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A two-stage framework for fair autonomous robot deployment using virtual forces

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TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE 2020年 141卷 35-50页

作者： Sallam, Gamal Baroudi, Uthman Temple Univ Philadelphia PA 19122 USA KFUPM Comp Engn Dept Dhahran Saudi Arabia

Consider a set of landmarks that are distributed in an emergency scene and each needs a specific number of robots in its vicinity. This paper presents a two-stage framework for deploying robots autonomously for such scenarios. In the first stage, a Two-hop Cooperative Virtual Force robot deployment (Two-hop COVER) technique is employed. It expedites the deployment process by establishing a cooperative relationship between robots and neighboring landmarks. Two-hop communication is utilized as well to reduce the deployment time and traveled distance by robots to satisfy the mission requirements and optimize the deployment process. However, in certain scenarios, Two-hop COVER may not achieve full demand satisfaction. Therefore, the second stage, called Trace Fingerprint is invoked to guarantee full satisfaction. Finally, a fairness-aware version of Two-hop COVER is presented to consider scenarios in which the mission requirements are greater than the available resources (i.e. robots) and hence, the fairness-aware approach dispatches robots in proportion to each landmark's need. Extensive simulation experiments have been carried out to assess the performance of the proposed framework. The simulation results demonstrate the effectiveness of the proposed approaches considering several performance factors, such as total travelled distance, total exchanged messages, total deployment time, and Jain's fairness index.

关键词： multi-robot deployment Dynamic coverage Cooperative deployment Cyber physical systems Intelligent transportation

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COVER: A Cooperative Virtual Force robot deployment Technique 15

COVER: A Cooperative Virtual Force Robot Deployment Techniqu...

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IEEE International Conference on Computer and Information

作者： Sallam, Gamal Baroudi, Uthman King Fahd Univ Petr & Minerals Dept Comp Engn Dhahran 31261 Saudi Arabia

ISBN: (纸本)9781509001545

We present a Cooperative Virtual Force robot deployment (COVER) technique. Virtual force (VF) technique appears as one of the prominent approaches to perform multi-robot deployment autonomously. However, most of the existing VF based approaches lack purposeful deployment. Our approach modifies the original VF approach to overcome this problem and considers the mission requirements such as the number of required robots in each locality (e.g., landmarks are distributed and each needs a specific number of robots in its vicinity). In addition, COVER expedites the deployment process by establishing a cooperative relation between robots and neighboring landmarks. Extensive simulation experiments have been carried out to assess the performance of COVER along with Hungarian deployment method (a centralized approach), the basic virtual force (BVF) and other recent proposed variations. The simulation results demonstrate the effectiveness of COVER for several performance factors such as total travelled distance, total exchanged messages and total deployment time.

关键词： Virtual Force robots multi-robot deployment Dynamic Coverage Cooperative deployment

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COVER: A Cooperative Virtual Force robot deployment Technique

COVER: A Cooperative Virtual Force Robot Deployment Techniqu...

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IEEE International Conference on Ubiquitous Computing and Communications

作者： Gamal Sallam Uthman Baroudi Computer Engineering Department King Fahd Univ. of Petroleum & Minerals Dhahran 31261 Saudi Arabia

ISBN: (纸本)9781509001552

关键词： Virtual Force robots multi-robot deployment Dynamic Coverage Cooperative deployment

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Signal-based deployment planning for robot teams in tunnel-like fading environments

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INTERNATIONAL JOURNAL OF robotICS RESEARCH 2013年第12期32卷 1381-1397页

作者： Rizzo, C. Tardioli, D. Sicignano, D. Riazuelo, L. Villarroel, J. L. Montano, L. Univ Zaragoza Aragon Inst Engn Res I3A Zaragoza Spain Ctr Univ Def Zaragoza Spain

Deploying a multi-robot team in confined environments poses multiple challenges that involve task and motion planning, localization and mapping, safe navigation, coordination of robots and also communications among all of them. In recent years, increasing attention has been paid to these challenges by the robotics community, but many problems remain unresolved. In this paper we address a technique for planning the deployment of a robot team in so-called fading environments, such as tunnels or galleries, where signal propagation presents specific characteristics. In order to maintain constant connectivity and high signal quality in the communication network formed by the robots and the base station, the robot deployment is driven by real-time signal measurements. First, an analysis of the signal propagation to obtain the general characteristic parameters of the signals in this kind of environment is carried out. Second, a technique which uses these parameters to drive the deployment is developed. A general strategy for this kind of environment in which the signals exhibit similar behavior is implemented. A complete system involving all of the above-mentioned robotics tasks has been developed. Finally, the system has been evaluated by means of simulation and in a real scenario.

关键词： multi-robot deployment robot motion planning fading environment communication signal propagation

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