Networked Robotic Systems Research Articles

Impulsive tracking synchronization control of networked robotic manipulator systems in the task space

This study investigates the impulsive tracking synchronization control of networked robotic manipulator systems based on Lagrangian systems. In the task space, the end-effector positions of networked robotic manipulators can synchronize and track a desired trajectory by designing an impulsive controller. Based on impulsive control, some algebraic synchronization criteria are derived. As a direct application of the theoretical results, tracking synchronization of six double-link robotic manipulators in the task space is discussed in detail. Numerical simulations are given to demonstrate the effectiveness and feasibility of the proposed control strategy.

Hierarchical prescribed-time ESO-based fault-tolerant controller synthesis for error-constrained coordination of networked robotic systems

Hierarchical prescribed-time ESO-based fault-tolerant controller synthesis for error-constrained coordination of networked robotic systems

Adaptive event-triggered security control for networked teleoperation systems.

An adaptive event-triggered security control method is proposed for networked robotic teleoperation systems subject to time-varying delays and false data injection (FDI) attacks. An event-triggered scheme is designed via the position and velocity signals of the master and slave robots, where the triggering thresholds can change adaptively with the system states. The position and velocity triggered signals and the feedback error between the operator and the environment forces are utilized to detect whether the transmitted signals suffered from FDI attacks. Then, a switching controller is designed, which is able to adopt the corresponding control strategy according to the corresponding detection result. The stability of the system and the convergence of the tracking errors are proved through Lyapunov functions, and the proposed method is validated through practical experiments. The proposed method is able to adaptively adjust the triggering frequency and effectively reduce the transmitted data, thus saving the network resources. Meanwhile, it can ensure the stability of networked teleoperation systems under time-varying delays and FDI attacks, as well as the position and force tracking performance.

A covert attack detection strategy combining physical dynamics and effective features-based stacked transformer for the networked robot systems

A covert attack detection strategy combining physical dynamics and effective features-based stacked transformer for the networked robot systems

Multiple symmetric task control for networked robot systems over switching network topology

AbstractThis article addresses the multiple symmetric task control issue of networked robot systems modeled by the Euler–Lagrange equation under a switching communication network topology. A distributed coordinated control protocol is presented with the aid of multiple virtual leaders. Based on the special structure of the network topology, some geometric convergence criteria under which the network can realize multiple symmetric consensus is given. Finally, two simulations conducted on seven two‐link revolute arms and eleven mass agents are proposed to illustrate our design, respectively.

Group‐weighted oscillatory containment for multiple robots under heterogeneous cooperation and competition

AbstractThe group‐weighted containment (GWC) problem is studied for swarms of robots, where the information flow among agents is heterogeneous (weighted) cooperative‐competitive and the whole networked systems are composed of multiple different groups. Each group is formed by multiple harmonic oscillator leaders and multiple robot followers governed by Euler‐Lagrange (EL) equations. After introducing the definition of group‐weighted containment to the networked robot systems, the control algorithms for the agents containing followers and leaders are formulated over newly weighted cooperative‐competitive network. Some necessary conditions for solving the weighted containment control problem are established. It is shown that the followers in every group can achieve a kind of novel coordinated behaviors. Specifically, the followers can converge to the dynamic convex hull spanned by the corresponding leaders' weighted coordinates under some conditions. Simulation results are provided to illustrate the effectiveness of the proposed control schemes.

Estimator-based multi-target tracking of networked robotic systems via predefined-time hierarchical control method

In this paper, we study the multi-target tracking problem of networked robotic systems (NRSs) within predefined time under a directed interaction topology considering disturbances and physical parameter uncertainties. On the basis of non-singular sliding-mode surface, a new predefined-time estimator-based hierarchical control algorithm is put forward so as to address the tracking problem under the case of multiple moving targets. Using the time base generator (TBG), a distributed estimator algorithm is designed to ensure that the followers can estimate different target states within a predefined-time. Certain sufficient conditions of predefined-time multi-target tracking of NRSs are presented using the Lyapunov stability and neighbor information interaction principle. In the end, numerical simulation experiments are offered to indicate the availability and correctness of the theoretical results.

Static group-bipartite consensus in networked robot systems with integral action

With the increasing complexity of modern industry, the traditional single-target control of swarm robots can no longer meet application requirements. Hence, this article addresses compound task control for swarm robot systems, where the control aim and the dynamics of the robot are modeled by static group-bipartite consensus and Euler–Lagrange systems, respectively. After introducing the concept of static group-bipartite consensus in networked Euler–Lagrange systems, a distributed group-bipartite consensus control protocol with integral action is designed, and the criterion that ensures that static group-bipartite consensus is reached is presented. The most remarkable feature of the proposed algorithm is that it can accurately calculate the final state of system convergence. Finally, simulation examples are presented to verify the theoretical results.

Oscillatory Group-Bipartite Consensus in a Swarm of Robots With Multiple Oscillatory Leaders

This article addresses the oscillatory group- bipartite consensus control problem for multiple robots modeled by the Euler–Lagrange equation with multiple oscillatory leaders. After introducing the definition of oscillatory group-bipartite consensus to the networked robot systems, an oscillatory group-bipartite consensus control protocol is provided by thoroughly exploiting the network topology. A new form of the Laplacian matrix involving the connection between agents is constructed that contains three parts, the weights between the agents from the oscillatory virtual leaders to the robot followers and the weights from the same subgroup and from different subgroups. The elements of each part have their own unique definition according to their characteristics. Moreover, a coordinate transformation is conducted based on such Laplacian matrix for stability analysis of controlled systems. Some criteria that ensure the swarm robots converge to oscillatory group-bipartite consensus are presented. Two simulations conducted under two typical group structure network topologies are given to validate the proposed control methodologies, respectively.

Synchronization control for multiple Euler–Lagrange systems in leader–follower framework under switching and event‐based communications

AbstractSynchronization control of network robotic systems has attracted numerous researches as the development of applying multi‐robotic systems in manufacturing. Despite the practical issues of networked systems such as dynamic connection and limited bandwidth, most of the previous results have been developed under the assumption that each robot knows the system desired trajectory, the interconnections between robots are fixed, and periodic communications. Thus, in this article, we study the synchronization control for networked robotic systems, modeled by Euler–Lagrange equation, under more general cases such that only a subgroup of the robots knows the desired trajectory and the communication between robots are switched. Particularly, first, we utilize an adaptive distributed observer algorithm for each robot to estimate the system trajectory (or the leader dynamics). Then the observer results are synthesized in the proposed control algorithm to enhance the synchronization of the robots. In addition, an event‐based algorithm is taken into account to reduce communication in case of no switching topology. Simulations with a network of four manipulators show that under the proposed control algorithms the synchronization of follower robots is achieved faster comparing with the relevant results in the literature.

Lag-Bipartite Formation Tracking of Networked Robotic Systems Over Directed Matrix-Weighted Signed Graphs.

This article studies the lag-bipartite formation tracking (LBFT) problem of the networked robotic systems (NRSs) with directed matrix-weighted signed graphs. Unlike the traditional formation tracking problems with only cooperative interactions, solving the LBFT problem implies that: 1) the robots of the NRS are divided into two complementary subgroups according to the signed graph, describing the coexistence of cooperative and antagonistic interactions; 2) the states of each subgroup form a desired geometric pattern asymptotically in the local coordinate; and 3) the geometric center of each subgroup is forced to track the same leader trajectory with different plus-minus signs and a time lag. A new hierarchical control algorithm is designed to address this challenging problem. Based on the Lyapunov stability argument and the property of the matrix-weighted Laplacian, some sufficient criteria are derived for solving the LBFT problem. Finally, simulation examples are proposed to validate the effectiveness of the main results.

Joint Communication–Motion Planning in Networked Robotic Systems

In the recent decade, many research efforts in robotic society have considered motion planning for maintaining connectivity in networked robotic system (NRS) by exploiting robotic autonomous mobility. On the other hand, cognitive radio (CR) in the communication society aims at fully exploiting the spectrum in a wireless network, while the motion planning is seldom considered, as a wireless device itself may not decide where to go. In this article, joint communication–motion planning (JCMP) is proposed to boost the capability of NRS by exploiting both the adaptive communications and mobility control of autonomous robots. Specifically, we propose a JCMP framework for NRS, which aims at jointly exploiting the degree-of-freedom in mobility, space, time, frequency and power dimensions from both the motion and communication components. Afterward, we design and evaluate JCMP in a conventional and a CR-relay-assisted robot system, which shows the capability of JCMP in improving the performance of NRS. Finally, we summarize the proposed JCMP-enabled NRS framework and provide a series of future research directions.

Transition from simple to complex contagion in collective decision-making

How does the spread of behavior affect consensus-based collective decision-making among animals, humans or swarming robots? In prior research, such propagation of behavior on social networks has been found to exhibit a transition from simple contagion—i.e, based on pairwise interactions—to a complex one—i.e., involving social influence and reinforcement. However, this rich phenomenology appears so far limited to threshold-based decision-making processes with binary options. Here, we show theoretically, and experimentally with a multi-robot system, that such a transition from simple to complex contagion can also be observed in an archetypal model of distributed decision-making devoid of any thresholds or nonlinearities. Specifically, we uncover two key results: the nature of the contagion—simple or complex—is tightly related to the intrinsic pace of the behavior that is spreading, and the network topology strongly influences the effectiveness of the behavioral transmission in ways that are reminiscent of threshold-based models. These results offer new directions for the empirical exploration of behavioral contagions in groups, and have significant ramifications for the design of cooperative and networked robot systems.

Robust formation control for networked robotic systems using Negative Imaginary dynamics

This paper proposes a consensus-based formation tracking scheme for multi-robot systems utilizing the Negative Imaginary (NI) theory. The proposed scheme applies to a class of networked robotic systems that can be modelled as a group of single integrator agents with stable uncertainties connected via an undirected graph. NI/SNI property of networked agents facilitates the design of a distributed Strictly Negative Imaginary (SNI) controller to achieve the desired formation tracking. A new theoretical proof of asymptotic convergence of the formation tracking trajectories is derived based on the integral controllability of a networked SNI systems. The proposed scheme is an alternative to the conventional Lyapunov-based formation tracking schemes. It offers robustness to NI/SNI-type model uncertainties and fault-tolerance to a sudden loss of robots due to hardware/communication fault. The feasibility and usefulness of the proposed formation tracking scheme were validated by lab-based real-time hardware experiments involving miniature mobile robots.

Introduction to the Special Section on Resilience in Networked Robotic Systems

The 17 papers in this special section focus on resilience in networked robotic systems. This collection of articles aims to provide a deeper understanding of resilience as it pertains to multirobot systems, and to disseminate the current advances in designing and operating networked robotic systems. We understand resilience to be a characteristic that enables amultirobot system to withstand or overcome unexpected adverse conditions or shocks, and unknown, unmodeled disturbances. It refers to the contingent nature of the robots’ behaviors that is aimed at preserving their functionality or minimizing the time periods during which their functionality is compromised. The papers explore new algorithmic and mathematical foundations toward resilience.

Safe and efficient process automation based on networked robot systems

This paper introduces the automation of transport operations in a logistics warehouse and excavation and loading operations in civil engineering by utilizing networked robot systems, which are robot systems based on networked control systems. The paper shows that safe and highly efficient automation can be achieved by relaxing the constraints on the robot’s perception and intelligence through communication networks.

Distributed Consensus Control of Networked Robotic Systems With Dynamic Leader Under Time-Varying Delays and Denial-of-Service Attacks

Consensus of multi-agent systems has a wide range of applications, such as coordination, cooperative transportation, and synchronization. This study investigates consensus control in the task space of multi-robotic systems modeled using Euler-Lagrange equations with a moving leading under time-varying delays and denial-of-service (DoS) attacks, respectively. Two control algorithms are studied when networked robotic systems are interconnected over directed spanning trees with a constant-velocity leader as the root. First, we use the Lyapunov-Razumikhin theorem to address a condition of the maximum time delay for nonuniform time-delay communication, thereby ensuring asymptotic tracking of the network. Second, we propose a novel resilient control framework to deal with DoS attacks. Note that designing the control algorithm for DoS attacks is difficult because the attacks cause signal discontinuity. The proposed resilient controller can release the DoS duration condition, which is a common requirement in many related works. It is verified that the consensus errors converge to the origin under the proposed control frameworks. We present experimental results to demonstrate the effectiveness of the proposed controllers.

A new consensus-based formation tracking scheme for a class of robotic systems using negative imaginary property

This brief proposes a consensus-based formation tracking scheme for multi-robot systems utilising the Negative Imaginary (NI) theory. The proposed scheme applies to a class of networked robotic systems that can be modelled as a group of single integrator agents with stable uncertainties connected via an undirected graph. NI/SNI property of networked agents facilitates the design of a distributed Strictly Negative Imaginary (SNI) controller to achieve the desired formation tracking. A new theoretical proof of asymptotic convergence of the formation tracking trajectories is derived based on the integral controllability of networked NI/SNI systems. The proposed scheme is an alternative to the conventional Lyapunov-based formation tracking schemes. It offers robustness to NI/SNI-type model uncertainties and fault-tolerance to a sudden loss of robots due to hardware/communication fault. The feasibility and usefulness of the proposed formation tracking scheme were validated by lab-based real-time hardware experiments involving miniature, two-wheeled mobile robots.

Some structural results for the problem of Min-Time Coverage in Constricted Environments

In a recent work, we introduced a new set of problems in the area of networked robotic systems that concern the time-optimal execution of certain coverage tasks taking place in constricted environments. That work provided the detailed problem definitions, a complete representation of these problems in terms of Mathematical Programming (MP) formulations, and a formal analysis of their worst-case computational complexity. The current work establishes some structural results for the considered problems that are useful for the strengthening of the aforementioned MIP formulations and for the further development of pertinent heuristic solution methods for these problems. We demonstrate the first possibility in this paper, and we defer the second one to future work.

Force-Reflecting Hierarchical Approach for Human-Aided Teleoperation of NRS With Event-Triggered Local Communication

In this article, we present a novel system architecture for teleoperation of the networked robotic system (NRS), involving several slave robots (i.e., followers) interconnected through event-triggered local communication, based on one/several long-distance communication links between a human-operated master robot (i.e., leader) and one/multiple followers. The control objective of such human-aided teleoperation problem is to force the master robot to track the slave ones in a fixed time under the human supervision, and meanwhile to drive all the slave ones to track the master in a fixed time, thus allowing the human operator to flexibly and remotely control the NRS. Another important concern in this article is to improve the telepresence of such system, i.e., to reconstruct the interaction force between followers and the task environment in the side of the human operator. To this end, a novel force-reflecting hierarchical control framework, involving the (local) dissipativity layer, (estimate) event-triggered layer, fixed-time force observer and neuroadaptive observer, is proposed. Based on the tools of hierarchical control analysis and Lyapunov stability, we derive several sufficient conditions for guaranteeing the fixed-time stability of the closed-loop dynamics. Finally, several experiments are performed to illustrate the performance of the proposed results.