Key Communication Technology In Multi-Agent Robotic System

Considerable attention has been devoted to utilize communication to improve the performance of coordination of multi-agent robotic system in the field of Multi-Agent System and Multi-Robot System. How to share information among multiply robots by communication is a key technique for coordination and cooperation. First of all, three communication methods in the decentralized control system are introduced. Then, the major topics and state-of-the-art of communication in the cooperation are summarized and reviewed. The methods of modelling the communicative decentralized control system are described and their advantages and shortcomings are analyzed and compared. The following are studied further.When communication is free, the central control model for coordination of the multi-agent robotic system is established after the representation of communication cost is parameterized. The presence of free communication reduces the computation complexity of multi-agent POMDPs to that of single-agent POMDPs. In this paper, a novel approximate algorithm, called Memetic algorithm based Q-Learning (MA-Q-Learning), is proposed as a means to solve the POMDP problems which has the uncertainty problems. The policies are evolved using memetic algorithms, whereas the improved Q-learning obtains predictive rewards to indicate fitness of the evolved policies. In order to solve the hidden state problem, historical information is incorporated with the current belief state to aid in finding the optimal policy. Finally, the search efficiency is improved by a hybrid search method, in which an adjustment factor is used to help keep the diversity of population and guide the crossover based on the combination of multiple kinds of crossover and mutation. The experiments conducted on benchmark datasets show that the proposed methodology is superior to other state-of-the-art POMDP approximate methods. Finally, the experiments on the coordination of multi-agent system validate the algorithm's effectiveness.Although the presence of free communication reduces the computation complexity of multi-agent POMDPs to that of single-agent POMDPs, in practice, communication is not free and reducing the amount of communication is often desirable. In order to reduce the amount of communication in the coordination of multi-agent robotic system, this paper presents a novel approach for making communication decision in a decentralized fashion, and the possible joint beliefs of the team are represented based on a directed acyclic graph. And communication is chosen only when an agent's local observations indicate that sharing information would lead to an increasing in expected reward. It is described how to apply centralized single-agent policies to decentralized multi-agent POMDPs by maintaining and reasoning over the possible joint beliefs of the team. Experiment and a detailed example show that the proposed DAG-DEC-COMM algorithm can reduce communication while improving the performance of distributed execution.Unreliable communication is a common feature of many real-world applications of multi-agent domains, especially of multi-agent robot system. Limited bandwidth, interference and loss of line-of-sight are some reasons why communication can fail. We introduce an improved Adopt algorithm for operating effectively over unreliable communication infrastructure in the context of the Distributed Constraint Optimization Problem (DCOP). The key idea in our approach is to let the improved algorithm reduce unnecessary communication and an adaptive mechanism of timeout is used in order to ensure the liveness to find the optimal solution. Thus, the number of messages communicated is decreased. Furthermore, the adaptive timeout can allow the algorithm to flexibly and robustly deal with message loss. Results show that with a few modifications, Adopt can be guaranteed to terminate with the optimal solution even in the presence of message loss and that time to solution degrades gracefully as message loss probability increases. The results also suggest that artificially introducing message loss even when communication infrastructure is reliable could be beneficial in terms of the amount of work agents need to do to find the optimal solution.Recent researches focus on multi-agent teamwork. Multi-agent human-robot team has applied to many fields. This paper investigates and develops a system of multi-agent human-robot with mobile information devices. Firstly, this paper presents the architecture of multi-agent human-robot with mobile devices, and designs and implements the communication system between human and robot and among robots. Information sharing is realized among the members of the team. Finally, the results of experiments show that this system is user-friendly and can effectively undertake the remote monitoring and control tasks and robot members of the team can construct the world model by communicating member's local environment information, which is beneficial to team coordination.