Optimal distributed interconnectivity of multi-robot systems by spatially-constrained clustering

2017 ◽  
Vol 25 (2) ◽  
pp. 96-113 ◽  
Author(s):  
Matin Macktoobian ◽  
Mahdi Aliyari Sh
Keyword(s):  
Clustering Algorithm ◽  
Task Assignment ◽  
Constrained Clustering ◽  
Loosely Coupled ◽  
Robot Systems ◽  
Multi Agent ◽  
Probabilistic Proof ◽  
Data Passing ◽  
Spatially Constrained Clustering ◽  
Multi Robot

A spatially-constrained clustering algorithm is presented in this paper. This algorithm is a distributed clustering approach to fine-tune the optimal distances between agents of the system to strengthen the data passing among them using a set of spatial constraints. In fact, this method will increase interconnectivity among agents and clusters, leading to improvement of the overall communicative functionality of the multi-robot system. This strategy will lead to the establishment of loosely-coupled connections among the clusters. These implicit interconnections will mobilize the clusters to receive and transmit information within the multi-agent system. In other words, this algorithm classifies each agent into the clusters with the lowest cost of local communication with its peers. This research demonstrates that the presented decentralized method will actually boost the communicative agility of the swarm by probabilistic proof of the acquired optimality. Hence, the common assumption regarding the full-knowledge of the agents’ primary locations has been fully relaxed compared to former methods. Consequently, the algorithm’s reliability and efficiency is confirmed. Furthermore, the method’s efficacy in passing information will improve the functionality of higher-level swarm operations, such as task assignment and swarm flocking. Analytical investigations and simulated accomplishments, corresponding to highly-populated swarms, prove the claimed efficiency and coherence.

scholarly journals Modelling and verification of reconfigurable multi-agent systems

2021 ◽  
Vol 35 (2) ◽  
Author(s):  
Yehia Abd Alrahman ◽  
Nir Piterman
Keyword(s):  
Model Checking ◽  
Communication Protocols ◽  
Local State ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Robot Systems ◽  
Message Exchange ◽  
Multi Agent ◽  
Exchange Data ◽  
Multi Robot

AbstractWe propose a formalism to model and reason about reconfigurable multi-agent systems. In our formalism, agents interact and communicate in different modes so that they can pursue joint tasks; agents may dynamically synchronize, exchange data, adapt their behaviour, and reconfigure their communication interfaces. Inspired by existing multi-robot systems, we represent a system as a set of agents (each with local state), executing independently and only influence each other by means of message exchange. Agents are able to sense their local states and partially their surroundings. We extend ltl to be able to reason explicitly about the intentions of agents in the interaction and their communication protocols. We also study the complexity of satisfiability and model-checking of this extension.

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 Automated Verification of Social Laws for Continuous Time Multi-Robot Systems

2019 ◽  
Vol 33 ◽  
pp. 7683-7690 ◽  
Author(s):  
Ronen Nir ◽  
Erez Karpas
Keyword(s):  
Continuous Time ◽  
Automated Verification ◽  
Shared Environment ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Temporal Planning ◽  
Social Law ◽  
Robot Systems ◽  
Multi Agent ◽  
Multi Robot

Designing multi-agent systems, where several agents work in a shared environment, requires coordinating between the agents so they do not interfere with each other. One of the canonical approaches to coordinating agents is enacting a social law, which applies restrictions on agents’ available actions. A good social law prevents the agents from interfering with each other, while still allowing all of them to achieve their goals. Recent work took the first step towards reasoning about social laws using automated planning and showed how to verify if a given social law is robust, that is, allows all agents to achieve their goals regardless of what the other agents do. This work relied on a classical planning formalism, which assumed actions are instantaneous and some external scheduler chooses which agent acts next. However, this work is not directly applicable to multi-robot systems, because in the real world actions take time and the agents can act concurrently. In this paper, we show how the robustness of a social law in a continuous time setting can be verified through compilation to temporal planning. We demonstrate our work both theoretically and on real robots.

scholarly journals 6G Mobile Communications for Multi-Robot Smart Factory

2021 ◽  
Author(s):  
Zhenyi Chen ◽  
Kwang-Cheng Chen ◽  
Chen Dong ◽  
Zixiang Nie
Keyword(s):  
Mobile Communication ◽  
Mobile Communications ◽  
Task Assignment ◽  
Wireless Networking ◽  
Smart Factory ◽  
Efficient Operation ◽  
Technical Requirements ◽  
Robot Systems ◽  
Robot Task ◽  
Multi Robot

Private or special-purpose wireless networks present a new technological trend for future mobile communications, while one attractive application scenario is the wireless communication in a smart factory. In addition to wireless technologies, this paper pays special attention to treat a smart factory as the integration of collaborative multi-robot systems for production robots and transportation robots. Multiple aspects of collaborative multi-robot systems enabled by wireless networking have been investigated, dynamic multi-robot task assignment for collaborative production robots and subsequent transportation robots, social learning to enhance precision and robustness of collaborative production robots, and more efficient operation of collaborative transportation robots. Consequently, the technical requirements of 6G mobile communication can be logically highlighted.

scholarly journals Engineering Challenges Ahead for Robot Teamwork in Dynamic Environments

2020 ◽  
Vol 10 (4) ◽  
pp. 1368
Author(s):  
Kurt Geihs
Keyword(s):  
Autonomous Robots ◽  
Conceptual Modeling ◽  
Dynamic Environments ◽  
Systems Perspective ◽  
Robot Systems ◽  
Multi Agent ◽  
Review State ◽  
Future Work ◽  
Theoretical Foundations ◽  
Multi Robot

The increasing number of robots around us creates a demand for connecting these robots in order to achieve goal-driven teamwork in heterogeneous multi-robot systems. In this paper, we focus on robot teamwork specifically in dynamic environments. While the conceptual modeling of multi-agent teamwork was studied extensively during the last two decades and commercial multi-agent applications were built based on the theoretical foundations, the steadily increasing use of autonomous robots in many application domains gave the topic new significance and shifted the focus more toward engineering concerns for multi-robot systems. From a distributed systems perspective, we discuss general engineering challenges that apply to robot teamwork in dynamic application domains and review state-of-the-art solution approaches for these challenges. This leads us to open research questions that need to be tackled in future work.

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