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On Combining multi-robot coverage and Reciprocal Collision Avoidance 1

12th International Symposium on Distributed Autonomous robotic Systems (DARS)

作者： Breitenmoser, Andreas Martinoli, Alcherio Univ So Calif Dept Comp Sci Robot Embedded Syst Lab Viterbi Sch Engn Los Angeles CA 90089 USA Ecole Polytech Fed Lausanne Sch Architecture Civil & Environm Engn Distributed Intelligent Syst & Algorithms Lab Lausanne Switzerland

ISBN: (数字)9784431558798

ISBN: (纸本)9784431558798;9784431558774

Although robotic coverage and collision avoidance are active areas of robotics research, the avoidance of collision situations between robots has often been neglected in the context of multi-robot coverage tasks. In fact, for robots of physical size, collisions are likely to happen during deployment and coverage in densely packed multi-robot configurations. For this reason, we aim to motivate by this paper the combined use of multi-robot coverage and reciprocal collision avoidance. We present a taxonomy of collision scenarios inmulti-robot coverage problems. In particular, coverage tasks with built-in heterogeneity such as multiple antagonistic objectives or robot constraints are shown to benefit from the combination. Based on our taxonomy, we evaluate four representative robotic use cases in simulation by combining the specific methods of Voronoi coverage and reciprocal velocity obstacles.

关键词： multi-robot coverage Voronoi tessellation Reciprocal collision avoidance Velocity obstacles Taxonomy of collision scenarios Evaluation of use cases

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Dynamic Frontier-Led Swarming:multi-robot Repeated coverage in Dynamic Environments

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 646-661页

作者： Vu Phi Tran Matthew A.Garratt Kathryn Kasmarik Sreenatha G.Anavatti School of Engineering and Information Technology University of New South WalesCanberraAustralian Capital Territory 2612Australia IEEE

A common assumption of coverage path planning research is a static *** environments require only a single visit to each area to achieve ***,some real-world environments are characterised by the presence of unexpected,dynamic *** require areas to be revisited periodically to maintain an accurate coverage map,as well as reactive obstacle *** paper proposes a novel swarmbased control algorithm for multi-robot exploration and repeated coverage in environments with unknown,dynamic *** algorithm combines two elements:frontier-led swarming for driving exploration by a group of robots,and pheromone-based stigmergy for controlling repeated coverage while avoiding *** tested the performance of our approach on heterogeneous and homogeneous groups of mobile robots in different *** measure both repeated coverage performance and obstacle avoidance *** a series of comparison experiments,we demonstrate that our proposed strategy has superior performance to recently presented multi-robot repeated coverage methodologies.

关键词： Artificial pheromones distributed control architecture dynamic obstacle avoidance multi-robot coverage stigmergy swarm robotics

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multi-robot Environmental coverage With a Two-Stage Coordination Strategy via Deep Reinforcement Learning

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2024年第6期25卷 5022-5033页

作者： Zhu, Lina Cheng, Jiyu Zhang, Hao Zhang, Wei Liu, Yuehu Xi An Jiao Tong Univ Inst Artificial Intelligence & Robot Xian 710049 Peoples R China Shandong Univ Sch Control Sci & Engn Jinan 250061 Shandong Peoples R China

multi-robot environmental coverage can be widely used in many applications like search and rescue. However, it is challenging to coordinate the robot team for high coverage efficiency. In this paper, we propose a Two-Stage Coordination (TSC) strategy, which consists of a high-level leader module and a low-level action executor. The former provides the robots with the topology and geometry of the environment, which are crucial for robots to learn "where" they should go and avoid invalid coverage. Based on the observed information and the environmental topology, the latter module takes primitive action to reach the sub-goal. To facilitate cooperation among the robots, we aggregate local perception information of neighbors from different hops based on graph neural networks. We compare our method with state-of-the-art multi-robot coverage approaches. Experiments and supporting ablation studies show the superior efficiency, scalability, and generalization of our algorithm especially in unseen style and scale of scenes, and an unseen number of robots.

关键词： Deep reinforcement learning multi-robot coverage goal-augmented POMDP

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Partitioning Strategies for multi-robot Area coverage with No Communication 14th

Partitioning Strategies for Multi-robot Area Coverage with N...

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14th International Conference on Intelligent Autonomous Systems (IAS)

作者： Nattero, Cristiano Mastrogiovanni, Fulvio Univ Genoa Genoa Italy

ISBN: (纸本)9783319480367;9783319480350

In this paper, we model topology-based partitioning strategies for multirobot area coverage with no communication as a balanced graph partitioning problem, which is subject to connectivity and reliability requirements. We formalise it as a combinatorial optimisation problem, propose a generalised formulation that encompasses its most relevant features, and we introduce two variants of the basic problem. Furthermore, we discuss a metaheuristic solutionmethod based on a hybrid Ant Colony Optimisation approach. Finally, the performance of the solution is validated using simulations.

关键词： Graph partitioning multi-robot coverage Ant colony optimisation

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Stigmergic coverage algorithm for multi-robot systems (demonstration) 12

Stigmergic coverage algorithm for multi-robot systems (demon...

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Proceedings of the 11th International Conference on Autonomous Agents and multiagent Systems - Volume 3

作者： Bijan Ranjbar-Sahraei Gerhard Weiss Ali Nakisaee Maastricht University MD Maastricht The Netherlands National Organization for Development of Exceptional Talents (NODET) Shiraz Iran

ISBN: (纸本)9780981738130

We demonstrate the realization of stigmergic coverage for multi-robot systems. Compared to current state-of-the-art algorithms for multi-robot coverage, our Stigmergy-based coverage algorithm (StiCo) has several key advantages. In particular, it does not need direct robot-robot communication. Moreover, this algorithm does not require any prior information about the environment. Simulation results illustrate robustness, scalability and simplicity of the algorithm.

关键词： multi-robot coverage stigmergy multi-agent systems

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2D-VPC: An Efficient coverage Algorithm for multiple Autonomous Vehicles

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2021年第8期19卷 2891-2901页

作者： Nair, Vishnu G. Guruprasad, K. R. Manipal Acad Higher Educ MAHE Manipal Inst Technol Dept Aeronaut & Automobile Engn Manipal 576104 Karnataka India Natl Inst Technol Karnataka Surathkal Dept Mech Engn Mangalore 575025 India

In this paper, we address a problem of multi-robotic coverage, where an area of interest is covered by multiple sensors, each mounted on an autonomous vehicle such as an aerial or a ground mobile robot. The area of interest is first decomposed into grids of equal size and then partitioned into Voronoi cells. Each robot/sensor is assigned the task of covering the corresponding Voronoi cell. We propose an optimal gridding size and partitioning methodology that eliminate the coverage inefficiencies induced by the partitioning process. We carried out experiments using multiple quadcopters and mobile robots to demonstrate and validate the proposed multi-sensor coverage strategy.

关键词： multi-robot coverage sensor coverage unmanned aerial vehicle Voronoi partition

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Distributed coverage of unknown/unstructured environments by mobile sensor networks

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3rd International Workshop on multi-robot Systems

作者： Rekleitis, I New, AP Choset, H Canadian Space Agency Canada DSO National Laboratories Singapore Singapore Mechanical Engineering Department Carnegie Mellon University United States

ISBN: (纸本)1402033885

In this paper we present an algorithmic solution for the distributed, complete coverage, path planning problem. Real world applications such as lawn mowing, chemical spill clean-up, and humanitarian de-mining can be automated by the employment of a team of autonomous mobile robots. Our approach builds on a single robot coverage algorithm. A greedy auction algorithm (a market based mechanism) is used for task reallocation among the robots. The robots are initially distributed through space and each robot is allocated a virtually bounded area to cover. Communication between the robots is available without any restrictions.

关键词： multi-robot coverage automated de-mining market-based approach Morse decomposition

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Distributed pursuit-evasion without mapping or global localization via local frontiers

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AUTONOMOUS robotS 2012年第1期32卷 81-95页

作者： Durham, Joseph W. Franchi, Antonio Bullo, Francesco Max Planck Inst Biol Cybernet Dept Human Percept Cognit & Act D-72076 Tubingen Germany Univ Calif Santa Barbara Dept Mech Engn Santa Barbara CA 93106 USA

This paper addresses a visibility-based pursuit-evasion problem in which a team of mobile robots with limited sensing and communication capabilities must coordinate to detect any evaders in an unknown, multiply-connected planar environment. Our distributed algorithm to guarantee evader detection is built around maintaining complete coverage of the frontier between cleared and contaminated regions while expanding the cleared region. We detail a novel distributed method for storing and updating this frontier without building a map of the environment or requiring global localization. We demonstrate the functionality of the algorithm through simulations in realistic environments and through hardware experiments. We also compare Monte Carlo results for our algorithm to the theoretical optimum area cleared as a function of the number of robots available.

关键词： Pursuit-evasion Clearing Cooperative robotics Distributed algorithms multi-robot coverage Surveillance Monitoring

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multi-robot Deployment using Topological Maps

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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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StiCo in Action 13

StiCo in Action

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International Conference on Autonomous Agents and multiagent Systems

作者： Bijan Ranjbar-Sahraei Sjriek Alers Karl Tuyls Gerhard Weiss Maastricht University Maastricht Netherlands

ISBN: (纸本)9781450319935

StiCo is a Stigmergic coverage approach, which is previously designed for dispersion of robots in a communication-limited environment. In contrast to the existing coverage approaches, StiCo does not rely on direct communication between robots, and does not require any data storage or computational power for the robots. The main building block of StiCo is using environmental markers for transferring information between robots. Therefore, in this paper the practical requirements for implementation of StiCo in a real world experiment with a swarm of e-pucks are described and the coverage behavior of StiCo is validated by various experiments.

关键词： Swarm robotics multi-robot coverage Stigmergy

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