scholarly journals A Survey and Analysis of Cooperative Multi-Agent Robot Systems: Challenges and Directions

2019 ◽  
Author(s):  
Zool Hilmi Ismail ◽  
Nohaidda Sariff
Keyword(s):  
Robot Systems ◽  
Multi Agent

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.

scholarly journals Design of fixed-time synchronization algorithm with applications

2019 ◽  
Vol 16 (6) ◽  
pp. 172988141989131
Author(s):  
Peng Zhang ◽  
Yongzheng Cong ◽  
Di Wu ◽  
Guorong Zhang ◽  
Qi Tan
Keyword(s):  
Time Synchronization ◽  
Lyapunov Stability Theory ◽  
Fixed Time ◽  
Homogeneous System ◽  
Synchronization Control ◽  
Multi Agent Systems ◽  
Time Control ◽  
Robot Systems ◽  
Electric Power Networks ◽  
Multi Agent

Fixed-time synchronization problem for a class of leader–follower multi-agent systems with second-order nonlinearity is studied in this article. A new fixed-time synchronization control algorithm is developed by effectively combining homogeneous system theory, Lyapunov stability theory, and fixed-time/finite-time control technology. The leader–follower multi-agent system is considered to achieve fixed-time synchronization control. Finally, numerical simulations including coordination control multiple pendulum robot systems and electric power networks are carried out to verify the control performance of the control strategy.

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.

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.

A Collision Prevention Technique for Multi-Agent Robot Systems with Topology Map

2016 ◽  
Vol 22 (11) ◽  
pp. 3469-3472
Author(s):  
GyeoungSeo Park ◽  
Hoeseok Yang
Keyword(s):  
Collision Prevention ◽  
Robot Systems ◽  
Multi Agent

Consensus Based Formation Control and Trajectory Tracing of Multi-Agent Robot Systems

2007 ◽  
Vol 48 (3) ◽  
pp. 397-410 ◽  
Author(s):  
Zhengping Wu ◽  
Zhihong Guan ◽  
Xianyong Wu ◽  
Tao Li
Keyword(s):  
Formation Control ◽  
Robot Systems ◽  
Multi Agent
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