In the field of mobile robotics, the study of multi-robot systems (MRSs) has grown significantly in size and importance in recent years. Having made great progress in the development of the basic problems concerning single-robot control, many researchers shifted their focus to the study of multi-robot coordination. This paper presents a systematic survey and analysis of the existing literature on coordination, especially in multiple mobile robot systems (MMRSs). A series of related problems have been reviewed, which include a communication mechanism, a planning strategy and a decision-making structure. A brief conclusion and further research perspectives are given at the end of the paper.

https://journals.sagepub.com/doi/pdf/10.5772/57313

A Survey and Analysis of Multi-Robot Coordination

The artificial potential field (APF) method is widely used for autonomous mobile robot path planning due to its simplicity and mathematical elegance. However, most researches are focused on solving the path-planning problem in a stationary environment, where both targets and obstacles are stationary. This paper proposes a new APF method for path planning of mobile robots in a dynamic environment where the target and obstacles are moving. Firstly, the new force function and the relative threat coefficient function are defined. Then, a new APF path-planning algorithm based on the relative threat coefficient is presented. Finally, computer simulation and experiment are used to demonstrate the effectiveness of the dynamic path-planning scheme.

An Evolutionary Artificial Potential Field Algorithm for Dynamic Path Planning of Mobile Robot

The paper presents research on the APF approach for solving the GNRON and local minima problems. The repulsive potential function is modified in order to solve the GNRON problem. A simulated annealing algorithm integrated into the APF has solved the local minimum problem. The improved APF is applied to the path-planning problem of soccer robots. The simulated experiments show the validity of this approach.

https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0263574703005666

Soccer robot path planning based on the artificial potential field approach with simulated annealing

Analyzing of the disadvantage of artificial potential field (APF) for mobile robot obstacle avoidance, local trap and vibrating, a new method for improving artificial potential field was proposed in this paper. A new force function was built and the simulation was done. It was approved from the simulation result that local trap was eliminated effectively and vibrating was mitigated but not eliminated through adjusting the parameters of the functions. Referencing to man driving car, the potential force area of mobile robot obstacle avoidance was limited and adjusted at any moment. The problem of mobile robot obstacle avoidance based-on APF was eliminated and the rapidness of arriving at the target was improved by this method.

Study of the New Method for Improving Artifical Potential Field in Mobile Robot Obstacle Avoidance

In this article we focus on the essential requirements of a robot for semantically dealing with cooperative problem solving in a natural setting such as discovery of exit from a labyrinth. A very common application area for such robots are used as set of multi-agents at junctions in Traffic Management and Information Systems (TMIS) to manage the traffic and interact with ambulance or fire fighters to traverse the shortest possible path [18]. In order to present the above mentioned goal, a new modular architecture for design and implementation of cooperative labyrinth discovery robots (CLDRs) is presented. The labyrinth data structure (Maze Set) is represented in notation 3 format useful for semantic logic data processing purposes. This facilitates semantic web services on each CLDR (agent). Each agent is an autonomous system which acts based on its sensors and information retrieved from other agents. Our aim is creating robotic agents based on semantic web services and implementing autonomous semantic agents (ASAs). Numerous domains are likely application areas for multiple ASAs (MASAs), such as systems for distributed control, decision support, and financial market projection. Initial application area will be "Cooperative Labyrinth Discovery" where MASA robots cooperatively inspect an uncharted maze to discover its exits. Hence, context awareness, semantic understanding, near area communication, and friend/foe distinction make up upper value sets loaded upon "automaton" nature of a robotic ASA. We are aiming at effecting coordination and cooperation among MASAs towards succeeding a shared goal through semantic web theory and techniques.

Human-Robot Interactive Communication Using Semantic Web Tech. in Design and Implementation of Collaboratively Working Robots

This paper summarizes the characteristics of soccer robot collision avoidance, and points out the disadvantages of traditional artificial potential field. An evolutionary artificial potential field is presented, in which the vector of velocity and acceleration are considered. The collision avoidance simulation is carried out to verify the reliability of tbe method.

Soccer robot collision avoidance control based on evolutionary artificial potential field

Autonomous robot soccer system consists of a multi-agent system that need to cooperate in unknown, dynamic, and competitive environment. Thus, it is a crucial issue how to realize effective and real time communications among soccer robots. There are three problems need to solve about the communication, they are dialog management, communication language, and communication protocol. Thereinto, communication language is a intermedium to transport information and exchange knowledge among agents. In this paper, we introduce the communication mechanism of autonomous robot soccer system, and its practical and reliable communication language based on KQML (Knowledge Query and Manipulation Language), which is designed for cooperative problem solving and knowledge sharing of the multi-robot system. It is shown that the communication mechanism is effective, efficient robust.

Design and realization of communication mechanism of autonomous robot soccer based on multi-agent system

Task allocation in multi-robot systems is one of the key themes in the study of robots.Summarization is presented in terms of classification,description and research situation of task allocation in multi-robot systems in this paper,and then some problems about task allocation in multi-robot systems are raised.

Progress of task allocation in multi-robot systems

Current application-driven demands are bringing us closer to the multirobot system which is on a larger scale and more complex However, most of the existing methods of task allocation for multirobot system ignore the inherent characteristics that complex tasks might have, taking the tasks as some can not be decomposed any more. A kind of complex tasks are depicted by limited task tree in this paper, and a complex task allocation algorithm based on market and limited task tree for multirobot system is presented. At the expense of increasing the solution cost a little bit, computation time is decreased greatly by restricting the decomposition. Experiment results show that this algorithm can achieve loosely-coupled task allocation quickly in multirobot systems in a wholly distributed way.

Task allocation based on market and limited-task tree for multirobot system

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Soccer robot collision avoidance control based on evolutionary artificial potential field

Design and realization of communication mechanism of autonomous robot soccer based on multi-agent system

Progress of task allocation in multi-robot systems

Task allocation based on market and limited-task tree for multirobot system