Networked Robotic Systems Research Articles

Practical Bipartite Tracking for Networked Robotic Systems via Fixed‐Time Estimator‐Based Control

In this paper, the fixed‐time practical bipartite tracking problem for the networked robotic systems (NRSs) with parametric uncertainties, input disturbances, and directed signed graphs is investigated. A new fixed‐time estimator‐based control algorithm for the NRSs is presented to address the abovementioned problem. By applying a sliding surface and the time base generator (TBG) approach, a new stability analysis method is proposed to achieve the fixed‐time practical bipartite tracking for the NRSs. We also derive the upper bound of the convergence time for employing the presented control algorithm to solve the practical bipartite tracking problem and further demonstrate that the convergence time is independent of the initial value. Finally, the simulation examples are given to verify the effectiveness of the presented algorithms.

Adaptive Formation Control of Networked Robotic Systems With Bearing-Only Measurements.

In this article, we address the bearing-only formation control problem of 3-D networked robotic systems with parametric uncertainties. The contributions of this article are two-fold: 1) the bearing-rigid theory is extended to solve the nonlinear robotic systems with the Euler-Lagrange-like model and 2) a novel almost global stable distributed bearing-only formation control law is proposed for the nonlinear robotic systems. Specifically, the robotic systems subject to nonholonomic constraints and dynamics are first transformed into a Euler-Lagrange-like model. By exploring the bearing-rigid graph theory, a backstepping approach is used to design the distributed formation controller. Simulations for 3-D robotics are given to demonstrate the effectiveness of the proposed control law. Compared to the distance-rigid formation control approach, the bearing-rigid approach guarantees almost global stability while naturally excluding flip ambiguities.

Second-order bipartite consensus for networked robotic systems with quantized-data interactions and time-varying transmission delays

This paper investigates the second-order bipartite consensus (BC) problems for networked robotic systems (NRSs) subject to model uncertainties and external disturbances over signed directed graphs. We have newly presented two classes of hierarchical control algorithms (HCAs) to solve the BC problems for NRSs in a more practical and challenging case of quantized-data interactions (QDIs) and time-varying transmission delays (TVTDs). By using Hurwitz criterion and Lyapunov stability argument, several sufficient conditions on control parameters are obtained and the BC performance of the regulated system is analyzed. Three examples validate the presented theoretical findings.

Task-space bipartite tracking of networked robotic systems via hierarchical finite-time control

Task-space bipartite tracking of networked robotic systems via hierarchical finite-time control

Discrete-Communication-Based Bipartite Tracking of Networked Robotic Systems via Hierarchical Hybrid Control

This paper investigates the bipartite tracking problem of networked robotic systems (NRSs) subject to input disturbances, discrete communications and signed directed graphs. Two new classes of hierarchical hybrid control algorithms (HHCAs), which involve both continuous and discontinuous signals in a uniform framework, are designed to solve the aforementioned problem in the model-independent control manner, i.e., without using the prior information of the system model. Besides, with the help of the Lyapunov statement and hybrid system theory, we establish several sufficient conditions for guaranteeing the convergence of the proposed hybrid algorithms. Finally, numerical examples are presented to illustrate the effectiveness of the proposed results.

Stability and Convergence of a Message-Loss-Tolerant Rendezvous Algorithm for Wireless Networked Robot Systems

This article considers the problem of swarm rendezvous when robots exchange local coordination messages through an unreliable wireless communication network (i.e., message-loss occurs). First, a discrete-time second-order consensus algorithm is provided to deal with the effects of unreliable channels on wireless networked robot (WNR) systems, and drive the robots to a given geometric formation. Then, necessary and sufficient conditions for the controlled WNR to converge to a desired formation, even in the presence of messages loss, are formulated and simulatively validated. The proposed conditions provide to the WNR designer a minimal topology connectivity requirement, and a relation among algorithm step-size and control gains to be fulfilled for guaranteeing swarm rendezvous.

Bipartite consensus for networked robotic systems with quantized-data interactions

The bipartite consensus problem of networked robotic systems (NRSs) with parametric uncertainties, input disturbances, and quantized-data interactions is addressed in this paper. Some novel distributed estimator-based control algorithms are designed to guarantee that all controlled robots can eventually reach bipartite consensus or their states asymptotically converge to the origin. By employing the Lyapunov argument and nonsmooth analysis theory, several sufficient criteria on control parameters for stabilizing the closed-loop systems and solving the aforementioned problems are provided. Finally, simulation examples are presented to illustrate the proposed algorithms.

Region-based flocking control for networked robotic systems with communication delays

Based on a self-tuning adaptive control gain technique, this paper proposes a novel adaptive controller to implement the region-based flocking control for the networked robotic systems with communication delays. It is shown that under the proposed control strategy, all the robots can always reach into the objective region, realize velocity matching and ensure collision avoidance, if the network topology graph is connected under certain initial position conditions. Some simulation results are provided to illustrate the effectiveness and robustness of the proposed novel controller.

Predictive control for visual servoing control of cyber physical systems with packet loss

Networked robotic visual servoing system is a representative cyber-physical system (CPS). This paper studies the robust predictive control problem of networked robotic visual servoing system with packet losses and uncertainty. Firstly, according to eye-to-hand framework, the system is modeled as a nonlinear discrete model with packet loss based on image-based visual servoing (IBVS) approach, where the packet losses obey a Bernoulli distribution. Since the discretization error of the system is a norm-bounded parameter, a nonlinear system with bounded uncertainty is derived. With regard to the principle of the MPC and the stochastic system method, the upper bound of the MPC performance index and the min-max optimization problem with uncertainty are presented. Based on robust least-square approach, the parameter-dependent predictive controller is obtained and an iterative algorithm is presented to solve the horizon optimization problem. Finally, numerical simulations and experiments are proposed to verify the effectiveness of the proposed algorithm.

Biologically-Inspired Learning and Adaptation of Self-Evolving Control for Networked Mobile Robots

This paper presents a biologically-inspired learning and adaptation method for self-evolving control of networked mobile robots. A Kalman filter (KF) algorithm is employed to develop a self-learning RBFNN (Radial Basis Function Neural Network), called the KF-RBFNN. The structure of the KF-RBFNN is optimally initialized by means of a modified genetic algorithm (GA) in which a Lévy flight strategy is applied. By using the derived mathematical kinematic model of the mobile robots, the proposed GA-KF-RBFNN is utilized to design a self-evolving motion control law. The control parameters of the mobile robots are self-learned and adapted via the proposed GA-KF-RBFNN. This approach is extended to address the formation control problem of networked mobile robots by using a broadcast leader-follower control strategy. The proposed pragmatic approach circumvents the communication delay problem found in traditional networked mobile robot systems where consensus graph theory and directed topology are applied. The simulation results and numerical analysis are provided to demonstrate the merits and effectiveness of the developed GA-KF-RBFNN to achieve self-evolving formation control of networked mobile robots.

Multi-objective region reaching control for a swarm of robots

This paper is concerned with the multi-objective region reaching control for a swarm of robots which are formulated by Lagrangian dynamics. Two distributed multi-objective region reaching control protocols are proposed for the networked robotic systems under directed acyclic topology, and a unifying methodology is presented to perform the convergence analysis for the robotic systems with static and moving target regions. The control strategy is developed by using the potential energy function approach, and the specified shapes of the various desired regions are constructed by selecting appropriate objective functions. In this control strategy, a network of a large number of robots evolves into multiple groups, and the robots in each group only require communicating with their neighbors. Thus, the proposed control strategy is effective for multi-objective region reaching control for a swarm of robots in practical applications. Finally, simulation examples are given to show the validity of the theoretical results.,

Project INSIDE: towards autonomous semi-unstructured human-robot social interaction in autism therapy.

This paper describes the INSIDE system, a networked robot system designed to allow the use of mobile robots as active players in the therapy of children with autism spectrum disorders (ASD). While a significant volume of work has explored the impact of robots in ASD therapy, most such work comprises remotely operated robots and/or well-structured interaction dynamics. In contrast, the INSIDE system allows for complex, semi-unstructured interaction in ASD therapy while featuring a fully autonomous robot. In this paper we describe the hardware and software infrastructure that supports such rich form of interaction, as well as the design methodology that guided the development of the INSIDE system. We also present some results on the use of our system both in pilot and in a long-term study comprising multiple therapy sessions with children at Hospital Garcia de Orta, in Portugal, highlighting the robustness and autonomy of the system as a whole.

Guest Editorial: Special section on “Foundations of resilience for networked robotic systems”

Guest Editorial: Special section on “Foundations of resilience for networked robotic systems”

Adaptive cooperative control of networked uncalibrated robotic systems with time‐varying communicating delays

This paper investigates the trajectory tracking control of the networked multimanipulator with the existence of time‐varying delays and uncertainties in both kinematics and dynamics. To address time‐varying delays in the communication links, a novel control scheme is established by the design of delay–rate‐dependent networking mutual coupling strengths. Besides, to handle the kinematic and dynamic uncertainties, an adaptive controller is designed. The proposed control scheme guarantees that the networked robotic system can track a commonly desired trajectory cooperatively with the strongly connected communication graph, uncertainties, and time‐varying communicating delays. A Lyapunov–Krasovskii functional is employed to rigorously prove the asymptotic convergence of both tracking errors and synchronization errors. The simulation results are provided to verify the effectiveness of the control method proposed by this paper.

Bearing-based formation control of networked robotic systems with parametric uncertainties

Abstract In this paper, the distributed bearing-based formation control problem for networked robotic systems with parametric uncertainties is investigated. Firstly, under the consideration that the task-space velocity is measurable, a reference control input is designed to achieve a bearing constrained target formation. For the unmeasurable task-space velocity case, an observer-based reference velocity scheme is proposed and only the local relative task-space position measurement is needed to achieve globally bearing-based formation stabilization. By designing a velocity feedback in proportional-integral reference velocity control scheme, at least two leaders can handle the leader–follower formation tracking problem, in which the followers do not need any global information. Finally, some simulation results are provided to demonstrate the effectiveness of the proposed control laws.

Adaptive synchronization control of networked robot systems without velocity measurements

SummaryThis paper addresses the adaptive synchronization control problem of networked robot systems characterized by the Lagrangian function, where exact dynamic models are unknown and velocity measurements are unavailable. A class of distributed observers, comprised of multiple dynamic variables and static variables, are established based on no a priori restriction on the boundness of the observer states. The observer is compatible for different control schemes with or without structure uncertainties. Using the estimated states given by the observer, adaptive distributed control input is developed, and then, closed‐loop dynamic models for filtered vectors are established. It is proven that our proposed control scheme permits global exact state estimation and global asymptotic synchronization while compensating for structure uncertainties. Simulations are provided to demonstrate the effectiveness of the results.

HoneyBot: A Honeypot for Robotic Systems

Historically, robotics systems have not been built with an emphasis on security. Their main purpose has been to complete a specific objective, such as to deliver the correct dosage of a drug to a patient, perform a swarm algorithm, or safely and autonomously drive humans from point A to point B. As more and more robotic systems become remotely accessible through networks, such as the Internet, they are more vulnerable to various attackers than ever before. To investigate remote attacks on networked robotic systems we have leveraged HoneyPhy, a physics-aware honeypot framework, to create the HoneyBot. The HoneyBot is the first software hybrid interaction honeypot specifically designed for networked robotic systems. By simulating unsafe actions and physically performing safe actions on the HoneyBot we seek to fool attackers into believing their exploits are successful, while logging all the communication to be used for attacker attribution and threat model creation. In this paper, we present the HoneyBot and discuss our proof of concept implementation. Our HoneyBot prototype swaps between physical actuation and using prebuilt models of sensor behavior for simulation at runtime given user input commands.

Coordinated tracking for networked robotic systems via model-free controller–estimator algorithms

This paper mainly focuses on two classes of coordinated tracking problems for networked robotic systems, including semi-global coordinated tracking (SCT) problem and global coordinated tracking (GCT) problem. Considering that the dynamics of the networked robotic system can be unattainable, several novel model-free controller-estimator algorithms are proposed to solve the SCT and GCT problems, as well as to reject the input disturbances contained in the system dynamics. By invoking nonsmooth analysis and Lyapunov argument, a number of novel criteria (including sufficient criteria, necessary and sufficient criteria) for semi-global and global asymptotic stability of the presented algorithms are established. Finally, simulation experiments are carried out to verify the theoretical results.

Distributed Coordination and Cooperation Control for Networked Mobile Manipulators

This paper addresses distributed coordination and cooperation control for networked mobile manipulators over a jointly connected topology with time delays. First, tracking control is proposed to guarantee the position and velocity synchronization of the networked mobile manipulators, while keeping a formation. For cooperation control, the decoupled dynamics is considered so that the task and null space of the mobile manipulators can be designed to achieve different missions. For end-effector motion, synchronization control works in combination with force controls to ensure that the network of mobile manipulators achieves cooperative manipulation and transportation. The motion of the mobile bases is controlled in the null space, which can be designed to track a trajectory, avoid colliding with obstacles, and achieve velocity consensus without influencing the main task. Numerical examples are addressed to demonstrate the performance of the proposed networked robotic system.

A Packet Loss Tolerant Rendezvous Algorithm for Wireless Networked Robot Systems

AbstractThis paper studies the coordination problem for a wireless networked robot (WNR) system. The objective is to drive the robots to keep a desired formation through local exchange of information. Nevertheless, packet losses may occur during communications among robots, thus preventing the system to reach its specific target. Specifically, the effects of an unreliable channel on the WNR performance are analyzed by considering the simulation of a corrective consensus algorithm into a network simulator. The use of a packet‐loss‐tolerant protocol is suggested to cope with heavy communication disruption. Network Simulator (NS‐3) simulation results validate the effectiveness of the proposed approach.