Distributed control of simulated autonomous mobile robot collectives in payload transportation

A behavior-based control paradigm that allows a distributed collection of autonomous mobile robots to control the lifting and lowering processes of payload transportation is proposed and then tested with computer simulations. This control paradigm, which represents an approach to solving the cooperative load-bearing problem inherent in multi-agent payload transportation, is based upon a control structure we term thebehavior pathway controller. The behavior pathway controller emphasizes simple, feasible methodologies over complex, optimal methodologies, although we show that with some global self-organization of the collective, the feasible solutions approach and become optimal solutions. Using this controller in simulated environments, our robots demonstrate an ability to function with inaccurate sensor data, which is an important consideration for real world implementations of an autonomous mobile robot control paradigm. The simulated robots also demonstrate an ability to learn their place, or role, within the collective. They must learn their relative roles because they possess no predetermined knowledge about pallet mass, pallet inertia, collective size, or their positions relative to the pallet's center of gravity.     

Lifelong Adaptation in Heterogeneous Multi-Robot Teams: Response to Continual Variation in Individual Robot Performance

Generating teams of robots that are able to perform their tasks over long periods of time requires the robots to be responsive to continual changes in robot team member capabilities and to changes in the state of the environment and mission. In this article, we describe the L-ALLIANCE architecture, which enables teams of heterogeneous robots to dynamically adapt their actions over time. This architecture, which is an extension of our earlier work on ALLIANCE, is a distributed, behavior-based architecture aimed for use in applications consisting of a collection of independent tasks. The key issue addressed in L-ALLIANCE is the determination of which tasks robots should select to perform during their mission, even when multiple robots with heterogeneous, continually changing capabilities are present on the team. In this approach, robots monitor the performance of their teammates performing common tasks, and evaluate their performance based upon the time of task completion. Robots then use this information throughout the lifetime of their mission to automatically update their control parameters. After describing the L-ALLIANCE architecture, we discuss the results of implementing this approach on a physical team of heterogeneous robots performing proof-of-concept box pushing experiments. The results illustrate the ability of L-ALLIANCE to enable lifelong adaptation of heterogeneous robot teams to continuing changes in the robot team member capabilities and in the environment.     

Cooperation without deliberation: A minimal behavior-based approach to multi-robot teams

While terminology and some concepts of behavior-based robotics have become widespread, the central ideas are often lost as researchers try to scale behavior to higher levels of complexity. “Hybrid systems” with model-based strategies that plan in terms of behaviors rather than simple actions have become common for higher-level behavior. We claim that a strict behavior-based approach can scale to higher levels of complexity than many robotics researchers assume, and that the resulting systems are in many cases more efficient and robust than those that rely on “classical AI” deliberative approaches. Our focus is on systems of cooperative autonomous robots in dynamic environments. We will discuss both claims that deliberation and explicit communication are necessary to cooperation and systems that cooperate only through environmental interaction. In this context we introduce three design principles for complex cooperative behavior—minimalism, statelessness and tolerance—and present a RoboCup soccer system that matches the sophistication of many deliberative soccer systems while exceeding their robustness, through the use of strict behavior-based techniques with no explicit communication.     

多智能体网络系统的自适应协调控制

为实现多智能体网络系统的协调控制,设计了一种新型的带有自适应协调器的控制器.基于动态图建立了多智能体网络系统的模型,并考虑了系统的非线性互联和不可避免存在的时变时滞.应用分布式控制策略,设计了自适应参数估计的协调器,用于调节智能体之间的互联强度,使网络达到稳定的预设水平.并基于Lyapunov-Kra-sovskii泛函和自适应动态偏差反馈控制技术,根据拉萨尔不变集原理证明了偏差控制系统的渐近收敛性.这种控制方法,可在系统参数不确定的情况下,同时完成参数估计和协调控制.所设计的控制律和自适应律简单,易于实现,仿真示例验证了所提方法的有效性.     

Artificial neural network based robot control: An overview

The current thrust of research in robotics is to build robots which can operate in dynamic and/or partially known environments. The ability of learning endows the robot with a form of autonomous intelligence to handle such situations. This paper focuses on the intersection of the fields of robot control and learning methods as represented by artificial neural networks. An in-depth overview of the application of neural networks to the problem of robot control is presented. Some typical neural network architectures are discussed first. The important issues involved in the study of robotics are then highlighted. This paper concentrates on the neural network applications to the motion control of robots involved in both non-contact and contact tasks. The current state of research in this area is surveyed and the strengths and weakness of the present approaches are emphasized. The paper concludes by indentifying areas which need future research work.     

A multi-agent architecture with cooperative fuzzy control for a mobile robot

The challenges of robotics have led the researchers to develop control architectures composed of distributed, independent and asynchronous behaviors. One way to approach decentralization is through cooperative control, since it allows the development of complex behavior based on several controllers combined to achieve the desired result. Robots, however, require high-level cognitive capacities, and multi-agent architectures provide the appropriate level of abstraction to define them. This article describes a multi-agent architecture combined with cooperative control developed within the agent. The experiments were carried out on an ActivMedia Pioneer 2DX mobile robot.     

Variable structure control for a wheeled mobile robot

This paper is concerned with a robust control for wheeled mobile robots. Mobile robots equipped with undeformable wheels are referred to as 'wheeled mobile robots' and constitute a typical example of non-holonomic systems, where the standard control algorithms developed for robotic manipulators without constraints are no longer applicable. It is shown using the formulation of a dynamic feedback linearization (DFL) methodology that a robust sliding mode controller is an efficient design tool to take into account stabilization and tracking control problems. Compared with previous studies based on DFL, the proposed method shows improvement of the trajectory tracking and stabilization process. The robustness is guaranteed in the presence of parameter uncertainty or unmodeled dynamics by the robust sliding mode control technique. Simulation results along with the conclusions drawn are discussed.     

动力学解析的四轮全向移动机器人电机解耦控制

四轮全向移动机器人是一个复杂的非线性、强耦合的机械系统,各轮驱动电机间存在强耦合现象,很难取得理想的控制效果。针对这一问题,提出一种基于动力学解析的多电机控制系统解耦方法。通过对四轮机器人的动力学解析推导出四轮转速与其驱动力矩间的状态方程,获得各电机输入输出量之间的耦合关系,在此基础上依据控制量一致思想设计解耦控制器,解决了传统参考模型解耦方法不能兼顾控制性能和解耦性能的问题,实现了四路电机的独立控制。仿真结果显示,该方法能够有效地减小控制系统各变量间的相互耦合作用,每路电机均很好地跟踪了各自的输入,解耦效果好。     

移动机器人编队控制的现状与问题

随着机器人向系统应用的方向发展，移动机器人编队控制问题成为研究的热点问题．为此，依据解决编队控制问题的不同思路，总结了编队控制的各种研究方法：基于行为法、人工势场法、跟随一领航法、虚结构法、循环法、模型预测控制法、分布式控制法，分别对几种编队控制方法的基本思想和特点进行总结和分析，最后从通用性、稳定性、鲁棒性和安全性等方面阐述了移动机器人编队控制理论与应用方面有待进一步研究的几个主要问题。     

A Flexible Control Architecture for Mobile Robots: An Application for a Walking Robot

To get the best features of both deliberative and reactive controllers, present mobile robot control architectures are designed to accommodate both types of controller. However, these architectures are still very rigidly structured thus deliberative modules are always assigned to the same role as a high-level planner or sequencer while low-level reactive modules are still the ones directly interacting with the robot environment. Furthermore, within these architectures communication and interface between modules are if not strongly established, they are very complex thus making them unsuitable for simple robotic systems. Our idea in this paper is to present a control architecture that is flexible in the sense that it can easily integrate both reactive and deliberative modules but not necessarily restricting the role of each type of controller. Communication between modules is through simple arbitration schemes while interface is by connecting a common communication line between modules and simple read and/or write access of data objects. On top of these features, the proposed control architecture is scalable and exhibits graceful degradation when some of the modules fail, similar to the present mobile robot architectures. Our idea has enabled our four-legged robot to walk autonomously in a structured uneven terrain.     

Distributed adaptive control for consensus tracking with application to formation control of nonholonomic mobile robots

In this paper, we investigate the output consensus problem of tracking a desired trajectory for a class of systems consisting of multiple nonlinear subsystems with intrinsic mismatched unknown parameters. The subsystems are allowed to have non-identical dynamics, whereas with similar structures and the same yet arbitrary system order. And the communication status among the subsystems can be represented by a directed graph. Different from the traditional centralized tracking control problem, only a subset of the subsystems can obtain the desired trajectory information directly. A distributed adaptive control approach based on backstepping technique is proposed. By introducing the estimates to account for the parametric uncertainties of the desired trajectory and its neighbors’ dynamics into the local controller of each subsystem, information exchanges of online parameter estimates and local synchronization errors among linked subsystems can be avoided. It is proved that the boundedness of all closed-loop signals and the asymptotically consensus tracking for all the subsystems’ outputs are ensured. A numerical example is illustrated to show the effectiveness of the proposed control scheme. Moreover, the design strategy is successfully applied to solve a formation control problem for multiple nonholonomic mobile robots.     

Adaptive control of nonlinear PID-based analog neural networks for a nonholonomic mobile robot

An adaptive controller of nonlinear PID-based analog neural networks is developed for the velocity- and orientation-tracking control of a nonholonomic mobile robot. A superb mixture of a conventional PID controller and a neural network, which has powerful capability of continuously online learning, adaptation and tackling nonlinearity, brings us the novel nonlinear PID-based analog neural network controller. It is appropriate for a kind of plant with nonlinearity uncertainties and disturbances. Computer simulation for a differentially driven nonholonomic mobile robot is carried out in the velocity- and orientation-tracking control of the nonholonomic mobile robot. The effectiveness of the proposed control algorithm is demonstrated through the simulation experiment, which shows its superior performance and disturbance rejection.     

Robust tracking control of nonholonomic dynamic systems with application to the bi-steerable mobile robot

A tracking controller for nonholonomic dynamic systems is proposed which allows global tracking of arbitrary reference trajectories and renders the closed loop system robust with respect to bounded disturbances. The controller is based on [Chwa, D. (2004). Sliding-mode tracking control of nonholonomic wheeled mobile robots in polar coordinates. IEEE Transactions on Control Systems Technology, 12(4), 637-644] and shows several generalizations and improvements. The control law for tracking of general nonholonomic systems using inverse kinematic models (IKM) and sliding surfaces is stated. Conditions are proven under which robust tracking is achieved for a specific system. Tracking control is applied to the bi-steerable mobile robot, and simulation results are presented.     

Design,development, and control of a tough electrohydraulic hexapod robot for subsea operations

Abstract

In this paper, the design, the development, and the control for an 18 degree-of-freedom electrohydraulic hexapod robot for subsea operations are presented. The hexapod, called HexaTerra, can be equipped with a trenching machine, and move over obstacles and on sloped terrain. Optimization techniques are employed to size the robot legs. Rigid body equations of motion and hydraulic dynamics are developed. Compact electrohydraulic components are sized and selected taking into account the leg kinematics and system dynamic analysis. A model-based control system design is implemented in a real-time environment, able to produce the overall functionality and performance. Experimental results obtained from preliminary tests with the developed electrohydraulic hexapod show good controlled performance and demonstrate excellent system stability over obstacles.     

New approach to stochastic stability and controller design for networked control systems

This paper addresses the random time-delays and packet losses issues of networked control systems （NCS） within the framework of jump linear systems with mode-dependent time-delays. A new delay-dependent condition on the stochastic stability is proposed by a new stochastic Lyapunov-Krasovskii functional. The condition is formulated as a set of coupled linear matrix inequalities （LMIs）. As an example to verify the proposed method, an inverted-pendulum system with network is considered. The simulation results demonstrate the effectiveness of the method.     

Fault detection for networked control systems subject to quantisation and packet dropout

This article addresses the stochastic fault detection (SFD) problem in finite-frequency domain for a class of networked control systems (NCSs) with respect to signal quantisation and data packet dropout. Considering a logarithmic quantiser and Markovian packet dropout, the NCS is modelled as a Markov jump linear system (MJLS) with quantisation error. Further, a new definition of finite-frequency stochastic H _? index is given, which gives a measurement of sensitivity. Subsequently, sufficient conditions are derived to guarantee that the MJLS can achieve such a performance. By virtue of the obtained conditions, the fault detection filters (FDFs) are designed in finite-frequency domain, which are valid in characterising the disturbance attenuation performance and finite-frequency fault sensitivity performance. Finally, a simulation example is given to illustrate the method and its effectiveness.     

Supervised Autonomy: A Framework for Human-Robot Systems Development

In this paper we present a paradigm for robot control, Supervised Autonomy. Supervised Autonomy is a framework, which facilitates the development of human robot systems. The components which this framework embraces has been devised in a human-oriented manner, to augment users in accomplishing their task. The general concept of our paradigm is to incorporate supervisory control with a qualitative approach for the control of robots. Supervisory control does not rely on human users to perform all the basic functions of perception and action in a system. The approach we have taken shifts all basic autonomous functions to the physical robot agent, integrated with a set of qualitative instructions, in combination with a simple graphical user interface, and together with suitable feedback form the complete framework. Experimental results of applying this framework to the use of a mobile robot teleoperation system are presented. The system we have developed make extensive use of behavior-based control technology, embracing a number of real-time visual behaviours, together with a set of intuitive instructions designed for the navigation of a mobile robot.     

Cooperative line of sight target tracking for heterogeneous unmanned marine vehicle teams: From theory to practice

In this paper we present the principle of Cooperative Line Of Sight Target Tracking (CLOSTT) for Heterogeneous Unmanned Marine Vehicle Teams. Thereby CLOSTT is part of a control architecture developed to coordinate existing single heterogeneous autonomous marine vehicles as a team. Within this control architecture CLOSTT separately offers a solution to the task of following a moving underwater target with a team of unmanned marine vehicles.     

Predictive-repetitive control with constraints: From design to implementation

This paper addresses the design and implementation of predictive-repetitive control systems, including the case when constraints are imposed. The approach is based on a frequency response decomposition technique that detects the dominant frequency components of the reference signals and embeds them in the predictive-repetitive controller. Analysis and design make use of the frequency response of the closed-loop system and the choice of the structure of the repetitive controller is considered as a balance between the reduction of tracking errors and minimization of the effects on performance of unwanted elements, such as model uncertainty. The implementation of operational constraints on the amplitudes of the control signals, their increments and on the outputs is considered using an on-line solution constructed using quadratic programming and the identification of active constraints. Experimental results from application to a 2 degree-of-freedom robotic system are used to illustrate the design and implementation procedures developed.     

Distributed guaranteed cost control for aperiodic sampled-data networked interconnected systems: a switched system approach

This paper investigates the distributed guaranteed cost control problem for a class of networked interconnected control systems (NICSs) under aperiodic sampling. The NICSs with missing data and time-varying delay are modelled as an aperiodic sampled-data switched system with uncertainties. Then, sufficient conditions ensuring the exponential stability and guaranteed cost quadratic performance are presented by using the average dwell time approach. The distributed state feedback controller is designed by solving a set of LMIs. Finally, a simulation example is given to verify the effectiveness of the proposed method.