In practice, the dual constraints of limited interaction capabilities and system uncertainties make it difficult for large-scale multiagent systems (MASs) to achieve intelligent collaboration with incomplete local relative information. In this article, a review is conducted on the recent development of MASs intended for intelligent control, including consensus problem, formation control, and flocking control. Based on the limitations of the interaction level and the constraints of the individual system level, the published results on intelligent control are categorized into limited sensing-based control, event-based control, pinning-based control, resilient control, and collaborative control under system constraints. Also, the applications of intelligent control for MASs are presented, especially for robotics, complex networks, and transportation. Finally, a discussion is given about the challenges and future directions of research in this field.

A Survey on Intelligent Control for Multiagent Systems

Formation control and coordination of multiple unmanned ground vehicles in normal and faulty situations: A review

The domain of underwater wireless sensor networks (UWSNs) had received a lot of attention recently due to its significant advanced capabilities in the ocean surveillance, marine monitoring and application deployment for detecting underwater targets. However, the literature have not compiled the state-of-the-art along its direction to discover the recent advancements which were fuelled by the underwater sensor technologies. Hence, this paper offers the newest analysis on the available evidences by reviewing studies in the past five years on various aspects that support network activities and applications in UWSN environments. This work was motivated by the need for robust and flexible solutions that can satisfy the requirements for the rapid development of the underwater wireless sensor networks. This paper identifies the key requirements for achieving essential services as well as common platforms for UWSN. It also contributes a taxonomy of the critical elements in UWSNs by devising a classification on architectural elements, communications, routing protocol and standards, security, and applications of UWSNs. Finally, the major challenges that remain open are presented as a guide for future research directions.

https://www.mdpi.com/1424-8220/20/18/5393/pdf

A Survey on Underwater Wireless Sensor Networks: Requirements, Taxonomy, Recent Advances, and Open Research Challenges

Adaptive leader-following formation control with collision avoidance for a class of second-order nonlinear multi-agent systems

A key problem in the formation control of homogeneous multiagent systems is the collision-free convergence of the agent positions into a desired formation It is a typical NP-hard problem by considering the problem as optimizing the assignment of multiple destinations to the same number of agents deployed in an open space It becomes even harder if the collision avoidance is required during the motion of agents, and thus, a suboptimal but efficient solution is adequate The traditional methods make it by accurate preplanning of the motion trajectory of each single agent, or simply letting them reach an equilibrium as a tradeoff between the collision avoidance and the desired formation In this article, a distributed control algorithm embedded with an assignment switch scheme is proposed to guarantee that the asymptotic convergence to the desired formation is achieved with no collisions between agents By the proposed algorithm, the agents keep moving in straight lines toward their respective destinations until they are going to collide if they do not stop, at which moment the agents will communicate their information locally to switch their destination assignments so that they will continue to move in different directions and avoid potential collisions Distributed control rules are also defined to confine the motion space of each agent for collision avoidance It has been rigorously proven that the positions of all agents converge to the desired formation with no collision under random initial deployment In addition, a detailed parameter design procedure is provided for both setting and controlling of the formation Finally, Monte Carlo simulations and actual experiments in the outdoor environment are implemented and the results verify the effectiveness of the proposed algorithm

Convergent Multiagent Formation Control With Collision Avoidance

This paper proposes a decentralized behavior-based formation control algorithm for multiple robots considering obstacle avoidance. Using only the information of the relative position of a robot between neighboring robots and obstacles, the proposed algorithm achieves formation control based on a behavior-based algorithm. In addition, the robust formation is achieved by maintaining the distance and angle of each robot toward the leader robot without using information of the leader robot. To avoid the collisions with obstacles, the heading angles of all robots are determined by introducing the concept of an escape angle, which is related with three boundary layers between an obstacle and the robot. The layer on which the robot is located determines the start time of avoidance and escape angle; this, in turn, generates the escape path along which a robot can move toward the safe layer. In this way, the proposed method can significantly simplify the step of the information process. Finally, simulation results are provided to demonstrate the efficiency of the proposed algorithm.

Decentralized behavior-based formation control of multiple robots considering obstacle avoidance

This paper proposes algorithm for the obstacle detection and classification using a single laser scanner. In a measurement data from a laser scanner, there exist points with large differential value called singular points, which can be used to obtain the boundary of an obstacle such that obstacle information can be analyzed. On the other hand, measurement data include a lot of measurement error, which makes it difficult to analyze the accurate obstacle information. To solve this problem, the least square estimation algorithm is used to obtain the accurate information using a single laser scanner, by compensation for the measurement error. This algorithm can be used for the effective obstacle avoidance of mobile robots, and the experimental results are included to demonstrate the effectiveness of the propose algorithm.

Giroung Lee

Papers

Decentralized behavior-based formation control of multiple robots considering obstacle avoidance

Obstacle Detection and Classification Algorithm using a Laser Scanner

Object Classification Algorithm with Multi Laser Scanners by Using Fuzzy Method