Network-based reconfiguration routes for a self-reconfigurable robot

This paper presents a network-based analysis approach for the reconfiguration problem of a self-reconfigurable robot. The self-reconfigurable modular robot named ＂AMOEBA-I＂ has nine kinds of non-isomorphic configurations that consist of a configuration network. Each configuration of the robot is defined to be a node in the weighted and directed configuration network. The transformation from one configuration to another is represented by a directed path with nonnegative weight. Graph theory is applied in the reconfiguration analysis, where reconfiguration route, reconfigurable matrix and route matrix are defined according to the topological information of these configurations. Algorithms in graph theory have been used in enumerating the available reconfiguration routes and deciding the best reconfiguration route. Numerical analysis and experimental simulation results prove the validity of the approach proposed in this paper. And it is potentially suitable for other self-reconfigurable robots＇ configuration control and reconfiguration planning.     

Graph-based optimal reconfiguration planning for self-reconfigurable robots

The goal of optimal reconfiguration planning (ORP) is to find a shortest reconfiguration sequence to transform a modular and reconfigurable robot from an arbitrary configuration into another. This paper investigates this challenging problem for chain-type robots based on graph representations and presents a series of theoretical results: (1) a formal proof that this is an NP-complete problem, (2) a reconfiguration planning algorithm called MDCOP which generates the optimal graph-based reconfiguration plan, and (3) another algorithm called GreedyCM which can find a near-optimal solution in polynomial time. Experimental and statistical results demonstrate that the solutions found by GreedyCM are indeed near-optimal and the approach is computationally feasible for large-scale robots.     

Configuration representation and reconfiguration optimization for the reconfigurable robots with independent manipulation

Single module of the reconfigurable robots with independent manipulation can perform the actions of locomotion and manipulation. In conformity with the request for achieving autonomous operation in the unstructurized environment instead of fixed operation in the structurized environment, these robots are applied in the complicated and dangerous environment. The existing researches on the configuration theory focus on the reconfigurable robots with limited locomotion and the ones with independent locomotion, not being applicable to the reconfigurable robots with independent manipulation. The vector configuration is put forward, the research content of which contains the topology and locomotion direction of configuration, the posture and orientation and connection relation between modules. Module state vector and configuration state matrix are proposed for representation methodology for the swarm configuration of these reconfigurable robots, which supports transformation operation to represent and trigger behavior motion of the module and reconfiguration between configurations. Optimization algorithm of assembly reconfiguration applying workload as the optimization target is presented, as well as optimization algorithm of transformation reconfiguration applying the integration of posture orientation workload and connection workload. The result of optimization is the relation of state transformation between the initial configuration and the object one as the basic of reconfiguration plan and control. Supported by the National High-Tech Research and Development Program of China (Grant No. 2006AA04Z254) and the Scientific Research Fund for Doctor of Liaoning Provice (Grant No. 20071007)     

工业机器人的分布式控制系统设计

介绍了通用型工业机器人分布式控制系统的设计方案，总结了工业机器人控制系统设计所必须考虑的问题。分析说明：工业机器人分布式控制系统是一种比较理想的快速实时控制系统。     

ModRED: Hardware design and reconfiguration planning for a high dexterity modular self-reconfigurable robot for extra-terrestrial exploration

This paper presents a homogeneous modular robot system design based on four per-module degrees of freedom (DOF), including a prismatic DOF to increase the versatility of its reconfiguration and locomotion capabilities. The ModRED (Modular Robot for Exploration and Discovery) modules are developed with rotary-plate genderless single sided docking mechanisms (RoGenSiD) that allow chain-type configurations and lead towards hybrid-type configurations. Various locomotion gaits are simulated through the Webots robot simulator and implemented in the real ModRED system. This work also addresses the problem of dynamic reconfiguration in a modular self-reconfigurable robot (MSR). The self-reconfiguration problem is modeled as an instance of the graph-based coalition formation problem. We formulate the problem as a linear program that finds the “best” partition or coalition structure among a set of ModRED modules. The technique is verified experimentally for a variety of settings on an accurately simulated model of the ModRED robot within the Webots robot simulator. Our experimental results show that our technique can find the best partition with a reasonably low computational overhead.     

Distributed Control for 3D Metamorphosis

In this paper, we define Proteo as a class of three-dimensional (3D) metamorphic robotic system capable of approximating arbitrary 3D shapes by utilizing repeated modules. Each Proteo module contains embedded sensors, actuators and a controller, and each resides in a 3D grid space. A module can move itself to one of its open neighbor sites under certain motion constraints. Distributed control for the self-reconfiguration of such robots is an interesting and challenging problem. We present a class of distributed control algorithms for the reconfiguration of Proteo robots based on the goal-ordering mechanism. Performance results are shown for experiments of these algorithms in a simulation environment, and the properties of these algorithms are analyzed.     

Mobile robot navigation by a Distributed Vision System

This paper proposes aDistributed Vision System (DVS), which is an intelligent infrastructure for mobile robots consisting of manyvision agents (VAs) embedded in an environment. The system monitors the environment from various viewing points with the VAs, maintains the dynamic environment models, and provides various information to robots. Based on this concept, we have developed a prototype of the DVS which consists of sixteen vision agents and simultaneously navigates two robots in a model town.     

Hormone-Inspired Self-Organization and Distributed Control of Robotic Swarms

The control of robot swarming in a distributed manner is a difficult problem because global behaviors must emerge as a result of many local actions. This paper uses a bio-inspired control method called the Digital Hormone Model (DHM) to control the tasking and executing of robot swarms based on local communication, signal propagation, and stochastic reactions. The DHM model is probabilistic, dynamic, fault-tolerant, computationally efficient, and can be easily tasked to change global behavior. Different from most existing distributed control and learning mechanisms, DHM considers the topological structure of the organization, supports dynamic reconfiguration and self-organization, and requires no globally unique identifiers for individual robots. The paper describes the DHM and presents the experimental results on simulating biological observations in the forming of feathers, and simulating wireless communicated swarm behavior at a large scale for attacking target, forming sensor networks, self-repairing, and avoiding pitfalls in mission execution.     

Distributed nonlinear control of mobile autonomous multi-agents

This paper studies the distributed nonlinear control of mobile autonomous agents with variable and directed topology. A new distributed nonlinear design scheme is presented for multi-agent systems modeled by double-integrators. With the new design, the outputs of the controlled agents asymptotically converge to each other, as long as a mild connectivity condition is satisfied. Moreover, the velocity (derivative of the output) of each agent can be restricted to be within any specified neighborhood of the origin, which is of practical interest for systems under such physical constraint. The new design is still valid if one of the agents is a leader and the control objective is to achieve leader-following. As an illustration of the generality and effectiveness of the presented methodology, the formation control of a group of unicycle mobile robots with nonholonomic constraints is revisited. Instead of assuming the point-robot model, the unicycle model is transformed into two double-integrators by dynamic feedback linearization, and the proposed distributed nonlinear design method is used to overcome the singularity problem caused by the nonholonomic constraint by properly restricting the velocities. Simulation results are included to illustrate the theoretical results.     

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.     

Crystalline Robots: Self-Reconfiguration with Compressible Unit Modules

We discuss a robotic system composed of Crystalline modules. Crystalline modules can aggregate together to form distributed robot systems. Crystalline modules can move relative to each other by expanding and contracting. This actuation mechanism permits automated shape metamorphosis. We describe the Crystalline module concept and show the basic motions that enable a Crystalline robot system to self-reconfigure. We present an algorithm for general self-reconfiguration and describe simulation experiments.     

A distributed perception infrastructure for robot assisted living

This paper presents an ambient intelligence system designed for assisted living. The system processes the audio and video data acquired from multiple sensors spread in the environment to automatically detect dangerous events and generate automatic warning messages. The paper presents the distributed perception infrastructure that has been implemented by means of an open-source software middleware called NMM. Different processing nodes have been developed which can cooperate to extract high level information about the environment. Examples of implemented nodes running algorithms for people detection or face recognition are presented. Experiments on novel algorithms for people fall detection and sound classification and localization are discussed. Eventually, we present successful experiments in two test bed scenarios.     

基于分布式对象的分布式仿真

该文首先比较了进行分布式并行仿真的几种典型手段,在此基础上,指出了分布式对象的应用价值,并利用该技术,提出了一个可重用的分布式并行仿真框架。     

Adaptive reconfiguration of data networks using genetic algorithms

Genetic algorithms are applied to an important, but little investigated, network design problem, that of reconfiguring the topology and link capacities of an operational network to adapt to changes in its operating conditions. These conditions include: which nodes and links are unavailable; the traffic patterns; and the quality of service (QoS) requirements and priorities of different users and applications. Dynamic reconfiguration is possible in networks that contain links whose endpoints can be easily changed, such as satellite channels, terrestrial wireless connections, and certain types of optical connections. We report preliminary results that demonstrate the feasibility of performing genetic search quickly enough for online adaptation.     

Distributed disk-based algorithms for model checking very large Markov chains

In this paper we present data structures and distributed algorithms for CSL model checking-based performance and dependability evaluation. We show that all the necessary computations are composed of series or sums of matrix-vector products. We discuss sparse storage structures for the required matrices and present efficient sequential and distributed disk-based algorithms for performing these matrix-vector products. We illustrate the effectivity of our approach in a number of case studies in which continuous-time Markov chains (generated in a distributed way from stochastic Petri net specifications) with several hundreds of millions of states are solved on a workstation cluster with 26 dual-processor nodes. We show details about the memory consumption, the solution times, and the speedup. The distributed message-passing algorithms have been implemented in a tool called PARSECS, that also takes care of the distributed Markov chain generation and that can also be used for distributed CTL model checking of Petri nets.     

基于可配置技术的先验决策式侦察信号处理

面对日益复杂的电磁环境,为了对空间电磁信号进行实时精确监测,适应侦察系统小型化、低功耗的要求,设计实现了一种基于可配置技术的先验决策式侦察信号处理的工程化方案.构建了先验决策式可配置平台,在此基础之上设计实现了侦察信号处理系统.通过在已有的开发环境下进行系统测试,验证了该方法的可行性,兼顾了战略侦察与战术侦察的双重要求,节约系统资源,适合在机载和星载等侦察设备中应用.     

分布式防火墙下的分布式通信技术

传统分布式对象技术是针对Intranet环境而设计的,难以满足Internet环境或者需要穿越防火墙通信的网络环境。该文通过对XML-RPC和BEEP协议的研究,设计并实现了基于XML-RPC的分布式对象技术,解决了在分布式防火墙下的分布式通信问题。     

基于基因重组原理的遗传算法

为了克服标准遗传算法的早熟现象,提高遗传算法的全局收敛性,提出了一种基于基因重组原理的遗传算法。定义了新的反向逻辑交叉算子和随机逻辑交叉算子,用它们对染色体的部分基因实现交叉重组。实验结果表明,该算法比经典的遗传算法具有更好的收敛性和稳定性,其中随机移位逻辑交叉算子可看成是蝶形移位逻辑交叉算子和洗牌移位逻辑交叉算子的推广,从而推广了文献[2]的结果。     

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.