The influence of intra-group differences on the flocking and obstacle avoidance movement of multiagent systems

In multiagent systems, it can be hard to design individual models due to financial constraints and design challenges. Given this, most studies use the same models for each individual and fail to take into account intra-group differences. In this paper, the effects of differences within a group on flocking and obstacle avoidance movements are studied. Individual differences, group differences, and mutants are the most significant intra-group differences. The differences lie mostly in perceptual radius, inter-individual forces, and the ability to avoid obstacles and pursue goals. We designed a smooth and bounded hybrid potential function with indefinite parameters. This function satisfies the consistency control requirements of the three previously mentioned systems. It is also applicable to ordinary cluster systems without individual differences. As a result of the action of this function, the system has the advantages of rapid swarming and constant system connectivity during motion. Through theoretical analysis and computer simulation, we confirm the effectiveness of our theoretical class framework designed for a multi-agent system with internal differences.

Development of Experimental Multi-Robot System for Network Connectivity Controls

This paper reports some results of network connectivity control experiments using a multi-robot system which we developed. Although a lot of connectivity control algorithms for a multi-robot network are proposed, almost all of them are verified only on computer simulations or using experimental robots with centralized sensors and controllers. To execute experimental verifications of connectivity control algorithms on a distributed robotic system, we developed an experimental multi-robot system. Hardware installed on the robot and information flow from sensors to actuators are detailed. Some results of measurement experiments are shown to estimate accuracy to detect a neighbor position. Then, results of connectivity control experiments using the developed multi-robot system are discussed.

Distributed Estimation of Algebraic Connectivity

The measurement algebraic connectivity plays an important role in many graph theory-based investigations, such as cooperative control of multiagent systems. In general, the measurement is considered to be centralized. In this article, a distributed model is proposed to estimate the algebraic connectivity (i.e., the second smallest eigenvalue of the corresponding Laplacian matrix) by the approach of distributed estimation via high-pass consensus filters. The global asymptotic convergence of the proposed model is theoretically guaranteed. Numerical examples are shown to verify the theoretical results and the superiority of the proposed distributed model.

Connectivity-Preserving Synchronization of Time-Delay Euler-Lagrange Networks With Bounded Actuation

This paper proposes a strategy to overcome the threats posed to connectivity-preserving synchronization of Euler-Lagrange networks by time-varying delays and bounded actuation. It first introduces a suitable distributed negative gradient plus damping injection controller, based on which it establishes that the local connectivity of time-delay Euler-Lagrange networks can be preserved by appropriately regulating the interagent connections and increasing the damping injection locally. Yet, actuator saturation may impede the proper modulation of the interagent connections and the injection of sufficient damping and, thus, may threaten the maintenance of connectivity. This paper then develops an indirect coupling control framework which integrates the bounded actuation constraints into the control design. The framework endows every agent with a virtual proxy and couples initially adjacent agents through their virtual proxies. The interproxy couplings then tackle the time-varying delays while the agent-proxy couplings account for the saturation of actuators. Lyapunov-Krasovskii analysis proves that the indirect coupling strategy can drive time-delay Euler-Lagrange networks with bounded actuation to connectivity-preserving synchronization by limiting the energy of the agent-proxy and interproxy couplings according to the actuation constraints. Experiments with Geomagic Touch haptic robots validate the proposed designs compared to a conventional proportional plus damping controller.

Hierarchical Distributed Control for Global Network Integrity Preservation in Multirobot Systems

In this paper, we address a novel hierarchical distributed control (HDC) strategy for networked multirobot systems (MRSs). This strategy is developed on a geometric approach without requiring estimation of algebraic connectivity. It is originally based upon behavioral control, but upgraded by distributed node control with a mobility constraint for global network integrity preservation and distributed connectivity control with a local connectivity minimization strategy for network coverage expansion. Thanks to properties of HDC, a networked MRS is capable of achieving high performance with cooperative tasks. We have examined and evaluated our proposed method in both simulations with up to 100 simulated robots and real-world experiments with up to 14 real robots.

Multipoint Rendezvous in Multirobot Systems

Multirobot rendezvous control and coordination strategies have garnered significant interest in recent years because of their potential applications in decentralized tasks. In this paper, we introduce a coordinate-free rendezvous control strategy to enable multiple robots to gather at different locations (dynamic leader robots) by tracking their hierarchy in a connected interaction graph. A key novelty in this strategy is the gathering of robots in different groups rather than at a single consensus point, motivated by autonomous multipoint recharging and flocking control problems. We show that the proposed rendezvous strategy guarantees convergence and maintains connectivity while accounting for practical considerations such as robots with limited speeds and an obstacle-rich environment. The algorithm is distributed and handles minor faults such as a broken immobile robot and a sudden link failure. In addition, we propose an approach that determines the locations of rendezvous points based on the connected interaction topology and indirectly optimizes the total energy consumption for rendezvous in all robots. Through extensive experiments with the Robotarium multirobot testbed, we verified and demonstrated the effectiveness of our approach and its properties.

Collision avoidance for multiple Lagrangian dynamical systems with gyroscopic forces

This article introduces a novel methodology for dealing with collision avoidance for groups of mobile robots. In particular, full dynamics are considered, since each robot is modeled as a Lagrangian dynamical system moving in a three-dimensional environment. Gyroscopic forces are utilized for defining the collision avoidance control strategy: This kind of forces leads to avoiding collisions, without interfering with the convergence properties of the multi-robot system’s desired control law. Collision avoidance introduces, in fact, a perturbation on the nominal behavior of the system: We define a method for choosing the direction of the gyroscopic force in an optimal manner, in such a way that perturbation is minimized. Collision avoidance and convergence properties are analytically demonstrated, and simulation results are provided for validation purpose.

Decentralized Estimation and Control for Preserving the Strong Connectivity of Directed Graphs

In order to accomplish cooperative tasks, decentralized systems are required to communicate among each other. Thus, maintaining the connectivity of the communication graph is a fundamental issue. Connectivity maintenance has been extensively studied in the last few years, but generally considering undirected communication graphs. In this paper, we introduce a decentralized control and estimation strategy to maintain the strong connectivity property of directed communication graphs. In particular, we introduce a hierarchical estimation procedure that implements power iteration in a decentralized manner, exploiting an algorithm for balancing strongly connected directed graphs. The output of the estimation system is then utilized for guaranteeing preservation of the strong connectivity property. The control strategy is validated by means of analytical proofs and simulation results.

Edge-weighted consensus-based formation control strategy with collision avoidance

In this paper, a consensus-based control strategy is presented to gather formation for a group of differential-wheeled robots. The formation shape and the avoidance of collisions between robots are obtained by exploiting the properties of weighted graphs. Since mobile robots are supposed to move in unknown environments, the presented approach to multi-robot coordination has been extended in order to include obstacle avoidance. The effectiveness of the proposed control strategy has been demonstrated by means of analytical proofs. Moreover, results of simulations and experiments on real robots are provided for validation purposes.