Global behavior via cooperative local control

The purpose of this paper is twofold. First, we outline important issues in designing real-time controllers for robots with numerous sensors, actuators, and behaviors. We address these issues by implementing a behavior based controller on a sophisticated autonomous robot. Hence, this work provides a point of reference for the scalability, ease of design, and effectiveness of the behavior based control for complex robots. Second, we explore the viability of using cooperation among local controllers to achieve coherent global behavior. Our approach is to decompose a difficult control task for a complex robot into a multitude of simpler control tasks for robotic subsystems. We illustrate and examine the effectiveness of this approach via rough terrain locomotion using an autonomous hexapod robot. Traversing rough terrain is a good task to test the viability of this approach because it requires a considerable amount of leg coordination. We found that implementing a complicated global control task with cooperating local controllers can effectively control complex robots.Support for this research was provided in part by a NASA Graduate Student Researcher Program Fellowship administered through the Jet Propulsion Laboratory, by Jet Propulsion Laboratory grant 959333, and by the Advanced Research Projects Agency under Office of Naval Research contract N00014-91-J-4038.     

Multi-Agent System-Based Fuzzy Controller Design with Genetic Tuning for a Mobile Manipulator Robot in the Hand Over Task

This paper presents an application of the multi-agent system approach to a service mobile manipulator robot that interacts with a human during an object delivery and hand-over task in two dimensions. The base, elbow and shoulder of the robot are identified as three different agents, and are controlled using fuzzy control. The control variables of the controllers are linear velocity of the base, angular velocity of the elbow, and angular velocity of the shoulder. Main inputs to the system are the horizontal and vertical distances between the human and robot hands. These are input to all three agents. In developing the fuzzy control rules, effective delivery and avoidance of contact with humans, not to cause physical damage, are considered. The membership functions of the fuzzy controllers are tuned by using genetic algorithms. In tuning, the performance is calculated considering the distance deviation from the direct path, time spent to reach the human hand and energy consumed by the actuators. The proposed multi-agent system structure based on fuzzy control for the object delivery task succeeded in both effective and safe delivery.     

An inverse kinematics architecture enforcing an arbitrary number of strict priority levels

An efficient inverse kinematics solver is a key element in applications targeting the on-line or off-line postural control of complex articulated figures. In the present paper we progressively describe the strategic components of a very general and robust inverse kinematics architecture. We then present an efficient recursive algorithm enforcing an arbitrary number of strict priorities to arbitrate the fulfillment of conflicting constraints. Due to its local nature, the moderate cost of the solution allows this architecture to run within an interactive environment. The algorithm is illustrated on the postural control of complex articulated figures.     

Linear Time Stable PD Controllers for Physics-based Character Animation

In physics-based character animation, Proportional-Derivative (PD) controllers are commonly used for tracking reference motions in motor control tasks. Stable PD (SPD) controllers significantly improve the numerical stability of traditional PD controllers and support large gains and large integration time steps during simulation [TLT11]. For an articulated rigid body system with n degrees of freedom, all SPD implementations to date, however, use an O(n³) dense matrix factorization based method. In this paper, we propose a linear time algorithm for SPD computation, which is based on Featherstone's forward dynamics formulation for articulated rigid body systems in generalized coordinates [Fea14]. We demonstrate the performance advantage of our algorithm by comparing with both the conventional dense matrix factorization based method and an alternative sparse matrix factorization based method. We show that the proposed algorithm provides superior stability when controlling complex models at large time steps. We further demonstrate that our algorithm can improve the learning speed and quality of a Deep Reinforcement Learning (DRL) system for physics-based character animation.     

时延网络中 Euler-Lagrange 系统的分布式自适应协调控制

对一类含未知参数的Euler-Lagrange系统协调控制问题进行了研究, 提出了一种自适应控制算法. 该算法容许通信网络为最一般的伪强连通图, 并允许通信时延的存在. 对系统中领航者为静态和动态两种情况分别进行了研究, 设计了相应的控制器.研究结果表明,在仅有部分个体能够和领航者进行通信的情况下, 控制器能保证网络中其他个体最终和领航者趋于一致. 运用Lyapunov稳定性定理和Barbalat 定理等对自适应控制器的稳定性进行了证明,并利用数值仿真验证了算法的有效性.     

Decentralized and adaptive control of multiple nonholonomic robots for sensing coverage

This work deals with decentralized control of multiple nonholonomic mobile sensors for optimal coverage of a given area for sensing purposes. We assume a density function over the region to be covered, which can be viewed as a probability density of the phenomena to be sensed. The density function is unknown but assumed to be linearly parameterized with unknown parameter weights. We consider a second‐order dynamic model for the mobile agents and derive decentralized adaptive control laws to achieve optimal coverage of the region. We then consider the case where the dynamic model of the agents are not fully known, and then develop parameter adaptation laws to achieve the optimal coverage objective. We test the derived algorithms using simulations and compare our proposed controllers with kinematics‐based controllers. We find that the feedback control design based on the dynamic model performs significantly better than controllers solely relying on kinematic models. Furthermore, for the unknown dynamics case, our controller outperforms the nonadaptive controller with poor initial parameter estimates.     

Distributed containment control of multi‐agent systems with general linear dynamics in the presence of multiple leaders

This paper considers the containment control problems for both continuous‐time and discrete‐time multi‐agent systems with general linear dynamics under directed communication topologies. Distributed dynamic containment controllers based on the relative outputs of neighboring agents are constructed for both continuous‐time and discrete‐time cases, under which the states of the followers will asymptotically converge to the convex hull formed by those of the leaders if, for each follower, there exists at least one leader that has a directed path to that follower. Sufficient conditions on the existence of these dynamic controllers are given. Static containment controllers relying on the relative states of neighboring agents are also discussed as special cases. Copyright © 2011 John Wiley & Sons, Ltd.     

Synchronization of complex networks with coupling delays via adaptive pinning intermittent control

The problem of exponential synchronization for a class of general complex dynamical networks with nonlinear coupling delays by adaptive pinning periodically intermittent control is considered in this paper. We use the methods of the adaptive control, pinning control and periodically intermittent control. Based on the piecewise Lyapunov stability theory, some less conservative criteria are derived for the global exponential synchronization of the complex dynamical networks with coupling delays. And several corresponding adaptive pinning feedback synchronization controllers are designed. These controllers have strong robustness against the coupling strength and topological structure of the network. Using the delayed nonlinear system as the nodes of the networks, a numerical example of the complex dynamical networks with nonlinear coupling delays is given to demonstrate the effectiveness of the control strategy.     

时延复杂网络的自适应周期间歇同步控制

研究同时具有耦合时延和节点时延复杂网络的自适应周期间歇同步控制问题.运用 Lyapunov 稳定性理论,自适应控制、牵制控制和间歇控制方法,给出保证该时延复杂网络全局指数同步、且保守性更小的判定准则,并给出相应的自适应和牵制自适应间歇同步控制器设计,该控制策略对节点间的耦合强度和网络的拓扑结构等具有较强的鲁棒性.最后以时延非线性动力系统为节点对复杂网络进行数值仿真,验证了结论的正确性和有效性.     

Finite time distributed distance‐constrained shape stabilization and flocking control for d‐dimensional undirected rigid formations

Most of the existing results on distributed distance‐constrained rigid formation control establish asymptotic or exponential convergence. To further improve the convergence rate, we explain in this paper how to modify existing gradient controllers to obtain finite time stability. For point agents modeled by single integrators, the controllers proposed in this paper drive the whole formation to locally converge to a desired shape with finite settling time. We also show for undirected triangular formation shape control, if all the agents start with non‐collinear positions, then the formation will converge to the desired shape in finite time. For agents modeled by double integrators, the proposed controllers allow all agents to both achieve the same velocity and reach a desired shape in finite time. All controllers are totally distributed. Simulations are also provided to validate the proposed control strategies. Copyright © 2015 John Wiley & Sons, Ltd.     

Order-Preserved Preset-Time Cooperative Control: A Monotone System-Based Approach

This paper is concerned with order-preserved preset-time cooperative control of multi-agent systems with directed graphs. A novel monotone system-based approach is proposed to preserve the initial order of agents while guaranteeing the preset-time state agreement. Specifically, three different distributed controllers together with sufficient conditions are designed to realize leaderless consensus, leader-following consensus, and containment control, respectively. The proposed controllers facilitate preset-time deployment of agents in practical scenarios with collision avoidance requirement. Comparison studies through a numerical example are carried out to illustrate the effectiveness of the proposed controllers.      

Implementation of real-time distributed control for discrete event robotic systems using Petri nets

This article presents a systematic method of modeling and implementing real-time control for discrete-event robotic systems using Petri nets. Because, in complex robotic systems such as flexible manufacturing systems, the controllers are distributed according to their physical structure, it is desirable to realize real-time distributed control. In this article, the task specification of robotic processes is represented as a system control-level net. Then, based on the hierarchical approach, it is transformed into detailed subnets, which are decomposed and distributed into the local machine controllers. The implementation of real-time distributed control through communication between the system controller and the machine controllers on a microcomputer network is described for a sample robotic system. The proposed implementation method is sufficiently general, and can be used as an effective prototyping tool for consistent modeling, simulation, and real-time control of large and complex robotic systems.     

Coordinated circumnavigation by multiple agents under directed topology

ABSTRACT

This paper focuses on the coordinated circumnavigation problem for multiple agents with directed communication topology. All agents are required to be evenly spaced around a moving target, and orbit around it with prescribed radii and circular velocity. We divide the coordinated circumnavigation system into a cascaded system consisting of a standoff tracking subsystem and a spacing distribution subsystem. A tracking controller and an additional controller for the two subsystems are developed, respectively. The global uniform stability of the coordinated circumnavigation system is analysed using the cascaded control theory. The presented controllers render each individual agent circumnavigating the target with the desired requirements. More importantly, we show that the derived tracking controller is a general extension of existing controllers for single agent circumnavigation problem. Another feature of the proposed controllers is that the directed topology considered only needs to have a directed spanning tree. Furthermore, the proposed controllers take the velocity constraints into consideration, that is more rational for practical applications. Numerical simulations are provided to verify the effectiveness of the proposed methods.     

Sliding mode coordination control for multiagent systems with underactuated agent dynamics

In this paper, we develop a new integrated coordinated control and obstacle avoidance approach for a general class of underactuated agents. We use graph-theoretic notions to characterise communication topology in the network of underactuated agents as determined by the information flow directions and captured by the graph Laplacian matrix. Obstacle avoidance is achieved by surrounding the stationary as well as moving obstacles by elliptical or other convex shapes that serve as stable periodic solutions to planar systems of ordinary differential equations and using transient trajectories of those systems to navigate the agents around the obstacles. Decentralised controllers for individual agents are designed using sliding mode control approach and are only based on data communicated from the neighbouring agents. We demonstrate the efficacy of our theoretical approach using an example of a system of wheeled mobile robots that reach and maintain a desired formation. Finally, we validate our results experimentally.     

A3M: an agent architecture for automated manufacturing

This paper proposes a software architecture based on mobile agents for distributed process control applications. A set of agents is employed to handle, in a single manufacturing cell, automatic assignment of control tasks to controllers, monitoring of cell functionalities and dynamic cell reconfiguration. The agents operate in a two‐layered structure: at the highest level, the planning agents analyse the inputs of the system designer and automatically create the field agents, which operate at the lowest level and embed the control tasks to be executed. Field agents, which are mobile, are able to reach autonomously the controllers of the cell, in order to perform the control activity there. Exploiting the mobility enables a field agent to change its running device when the variation of the design parameters or a system fault requires a new task distribution. A load‐balancing algorithm is introduced, with the objective of assigning each field agent to a controller of the manufacturing cell in order to fairly distribute the computation load. The algorithm uses a branch‐and‐bound technique to explore all possible solutions and applies two heuristics to throw away non‐feasible solutions and select the best branch to analyse. The algorithm is designed to run on‐line in order to allow a fast task redistribution when a fault condition occurs in the process control environment. Copyright © 2008 John Wiley & Sons, Ltd.     

Animation of deformable models using implicit surfaces

The paper presents a general approach for designing and animating complex deformable models with implicit surfaces. Implicit surfaces are introduced as an extra layer coating any kind of structure that moves and deforms over time. Offering a compact definition of a smooth surface around an object, they provide an efficient collision detection mechanism. The implicit layer deforms in order to generate exact contact surfaces between colliding bodies. A simple physically based model approximating elastic behavior is then used for computing collision response. The implicit formulation also eases the control of the object's volume with a new method based on local controllers. We present two different applications that illustrate the benefits of these techniques. First, the animation of simple characters made of articulated skeletons coated with implicit flesh exploits the compactness and enhanced control of the model. The second builds on the specific properties of implicit surfaces for modeling soft inelastic substances capable of separation and fusion that maintain a constant volume when animated     

Constructing consensus controllers for networks with identical general linear agents

We use a high‐gain methodology to construct linear decentralized controllers for consensus, in networks with identical but general multi‐input linear time‐invariant (LTI) agents and quite‐general time‐invariant and time‐varying observation topologies. Copyright © 2010 John Wiley & Sons, Ltd.     

Combined Direct and Inverse Kinematic Control for Articulated Figure Motion Editing

A new approach for the animation of articulated figures is presented. We propose a system of articulated motion design which offers a full combination of both direct and inverse kinematic control of the joint parameters. Such an approach allows an animator to specify interactively goal-directed changes to existing sampled joint motions, resulting in a more general and expressive class of possible joint motions. The fundamental idea is to consider any desired-joint space motion as a reference model inserted into the secondary task of an inverse kinematic control scheme. This approach profits from the use of half-space Cartesian main tasks in conjunction with a parallel control of the articulated figure called the coach-trainee metaphor. In addition, a transition function is introduced so as to guarantee the continuity of the control. The resulting combined kinematic control scheme leads to a new methodology of joint-motion editing which is demonstrated through the improvement of a functional model of human walking.     

Genetic programming for articulated figure motion

We present an approach to articulated figure motion in which motion tasks are defined in terms of goals and ratings. The agents are dynamically-controlled robots whose behaviour is determined by robotic controller programs. The controller programs for the robots are evaluated at each time step to yield torque values which drive the dynamic simulation of the motion. We use the AI technique of genetic programming (GP) to automatically derive control programs for the agents which achieve the goals. This type of motion specification is an alternative to key framing which allows a highly automated, learning-based approach to generation of motion. This method of motion control is very general (it can be applied to any type of motion), yet it allows for specifications of the types of specific motion which are desired for a high quality animation. We show that complex, specific, physically plausible and aesthetically appealing motion can be generated using these methods.     

Spacecraft coordination control in 6DOF: Integrator backstepping vs passivity-based control

In this paper, we present three nonlinear control solutions for 6DOF spacecraft formation control, adopted from Euler-Lagrange system theory. The quaternion parametrization results in dual equilibrium points in the closed loop system, and the controllers are proved to render these uniformly asymptotically stable. We also present a theoretical comparison of the three control solutions, together with simulation results to visualize the performance of the controllers.