基于动态角色分配的一致性协同无人机编队控制

随着微电子技术、数字通信技术的飞速发展,无人机编队已应用到许多领域。针对无人机编队保持和编队中能耗问题,提出了一种基于动态角色分配的一致性协同无人机编队控制方法。根据无人机运动学模型设计了一种反馈线性化姿态控制器。在此基础上,基于长机僚机模式设计了一种一致性编队控制算法,提升了编队系统的鲁棒性。同时,设计了一种基于匈牙利算法动态角色分配方法,使多无人机在执行任务过程中可依据具体的周围环境情况来重新制定编队方案确定各无人机位置以此来缩小执行任务周期,同时减小整体能量消耗,并以5架无人机构成编队为例开展了编队飞行仿真分析。仿真结果表明,基于动态角色分配的一致性协同无人机编队控制算法保证了编队控制系统的控制精度和鲁棒性,有效地减小了整体的能量消耗。     

A neural framework for adaptive robot control

This paper investigates how dynamics in recurrent neural networks can be used to solve some specific mobile robot problems such as motion control and behavior generation. We have designed an adaptive motion control approach based on a novel recurrent neural network, called Echo state networks. The advantage is that no knowledge about the dynamic model is required, and no synaptic weight changing is needed in presence of time varying parameters in the robot. To generate the robot behavior over time, we adopted a biologically inspired approach called neural fields. Due to its dynamical properties, a neural field produces only one localized peak that indicates the optimum movement direction, which navigates a mobile robot to its goal in an unknown environment without any collisions with static or moving obstacles.     

A rigorous framework for interactive robot control

This paper presents a rigorous, analytical framework for interactive control methods such as stiffness and impedance control. This paper does not present a novel synthesis method for robot control design. Rather, it presents a proper framework to analyse controllers for robots whose purpose is to interact energetically with the environment. First geometrical tools are introduced that are used in kinematic and dynamic analysis of the spatio-mechanical systems common in robotics. 'Port behaviour' and 'behavioural deviation' are then defined both intuitively and rigorously. The utility of this framework is demonstrated by a non-trivial example. Concepts of the behavioural approach are used.     

A column generation heuristic for a dynamic generalized assignment problem

This paper studies the dynamic generalized assignment problem (DGAP) which extends the well-known generalized assignment problem by considering a discretized time horizon and by associating a starting time and a finishing time with each task. Additional constraints related to warehouse and yard management applications are also considered. Three linear integer programming formulations of the problem are introduced. The strongest one models the problem as an origin–destination integer multi-commodity flow problem with side constraints. This model can be solved quickly for instances of small to moderate size. However, because of its computer memory requirements, it becomes impractical for larger instances. Hence, a column generation algorithm is used to compute lower bounds by solving the linear program (LP) relaxation of the problem. This column generation algorithm is also embedded in a heuristic aimed at finding feasible integer solutions. Computational experiments on large-scale instances show the effectiveness of the proposed approach.     

A generalized framework for interactive dynamic simulation for multirigid bodies

This paper presents a generalized framework for dynamic simulation realized in a prototype simulator called the Interactive Generalized Motion Simulator (I-GMS), which can simulate motions of multirigid-body systems with contact interaction in virtual environments. I-GMS is designed to meet two important goals: generality and interactivity. By generality, we mean a dynamic simulator which can easily support various systems of rigid bodies, ranging from a single free-flying rigid object to complex linkages such as those needed for robotic systems or human body simulation. To provide this generality, we have developed I-GMS in an object-oriented framework. The user interactivity is supported through a haptic interface for articulated bodies, introducing interactive dynamic simulation schemes. This user-interaction is achieved by performing push and pull operations via the PHANToM haptic device, which runs as an integrated part of I-GMS. Also, a hybrid scheme was used for simulating internal contacts (between bodies in the multirigid-body system) in the presence of friction, which could avoid the nonexistent solution problem often faced when solving contact problems with Coulomb friction. In our hybrid scheme, two impulse-based methods are exploited so that different methods are applied adaptively, depending on whether the current contact situation is characterized as "bouncing" or "steady." We demonstrate the user-interaction capability of I-GMS through on-line editing of trajectories of a 6-degree of freedom (dof) articulated structure.     

A unifying framework for robot control with redundant DOFs

Recently, Udwadia (Proc. R. Soc. Lond. A 2003:1783–1800, 2003) suggested to derive tracking controllers for mechanical systems with redundant degrees-of-freedom (DOFs) using a generalization of Gauss’ principle of least constraint. This method allows reformulating control problems as a special class of optimal controllers. In this paper, we take this line of reasoning one step further and demonstrate that several well-known and also novel nonlinear robot control laws can be derived from this generic methodology. We show experimental verifications on a Sarcos Master Arm robot for some of the derived controllers. The suggested approach offers a promising unification and simplification of nonlinear control law design for robots obeying rigid body dynamics equations, both with or without external constraints, with over-actuation or underactuation, as well as open-chain and closed-chain kinematics.

一种通过模糊自调整应用于机械手广义力/位置控制的稳定系统研究

提出一种基于模糊自调整的机械手控制结构,并针对机械手与外界环境接触时产生的作用力,定义了一种广义力,它是机械手执行机构输出力与机械手末端受到外界力的合力。那么,就可以用类似于机械手位置控制的方法达到力/位置控制目的,通过模糊自调整方法实现。在机械手受到的外力是有界限的前提下,考虑机械手非线性、耦合和多变量的动态特征,证明了整个闭环系统是全局稳定的。     

Robust implementation of generalized impedance control for robot manipulators

Compliant manipulation requires the robot to follow a motion trajectory and to exert a force profile while making compliant contact with a dynamic environment. For this purpose, a generalized impedance in the task space consisting of a second-order function relating motion errors and interaction force errors is introduced such that force tracking can be achieved. Using variable structure model reaching control, the generalized impedance is realized in the presence of parametric uncertainties. The proposed control method is applied to a multi-d.o.f. robot for an assembly task of inserting a printed circuit board into an edge connector socket. It is suggested that an assembly strategy which involves a sequence of planned target generalized impedances can enable the task to be executed in a desirable manner. The effectiveness of this approach is illustrated through experiments by comparing the results with those obtained using a model-based control implementation.     

基于PVR技术的机器人动态仿真控制

详细分析了基于投射式虚拟现实技术的机器人动态仿真控制,提出了仿真控制系统的总体框架,实现了仿真任务,并对投射式虚拟现实技术进行了改进,就投射式虚拟现实技术在一般工程仿真中的应用进行了有益的探讨.     

移动机器人编队的运动控制策略

为实现移动机器人编队的多样性、稳定性和队形变换连续性,并解决移动机器人编队运动中的避障、避碰、到达目标的问题,对基本队形进行分析,提出队形参数化的思路,建立基本队形虚结构的参数化数学模型,通过调整参数使队形在基本队形及其衍生的队形间进行变换;机器人在运行的过程中,利用行为融合方法、跟随领航者法、人工势场法和虚结构法对机器人进行运动控制,实现了机器人的避障、避碰、队形归建等目标。对上述策略进行了仿真实验,实验结果表明,使用本策略既保留了虚结构法队形稳定、队形归建迅速的优点,又改进了其灵活性差的不足。     

A generalized LPV system analysis and control synthesis framework

In this paper, a new approach for linear parameter-varying (LPV) system analysis and control synthesis is proposed. This unified framework combines two seemingly diversified methods in systematic gain-scheduling, LPV control theory, and extends the applicability of full block S -procedure to a general class of LPV systems. An example is used to demonstrate the proposed general LPV design approach, and to show its relative merits compared to other systematic gain-scheduling control techniques.     

A geometric framework for pole assignment algorithms

The problem of pole assignment by gain output feedback or by low-order dynamical compensator is considered from a geometric point of view. This makes it possible to unify, in a general framework, most of the existing pole assignment methods formulated in a state-space context, such as the minimal-order observers, the Brasch-Pearson compensator, and the methods proposed by H. Kimura, and to simplify their presentation. Moreover, new pole assignment algorithms may be derived from this general formulation     

Linearized dynamic models for trajectory control of robot manipulators

To make an appropriate choice of linear model for the development of real-time control of robot manipulators, four direct linearization schemes have been studied here on the basis of computation and accuracy. Accuracy is assured in the state linearization method, whereas the rate linearization method leads to a satisfactory trade-off between computational effort and accuracy. In the case of high-velocity motions, a combination of state and rate linearization is proposed.     

Artificial moment method for swarm robot formation control

The purpose of this paper is to develop a general control method for swarm robot formation control. Firstly, an attraction-segment leader-follower formation graph is presented for formation representations. The model of swarm robot systems is described. According to the results and two kinds of artificial moments defined as leader-attraction moment and follower-attraction moment, a novel artificial moment method is proposed for swarm robot formation control. The principle of the method is introduced and the motion controller of robots is designed. Finally, the stability of the formation control system is proved. The simulations show that both the formation representation graph and the formation control method are valid and feasible.     

移动机器人编队自修复的切换拓扑控制

针对机器人缺失后的移动机器人编队自修复问题, 构建了结合切换拓扑和交互动力模型的移动机器人编队模型, 通过分析机器人缺失后的拓扑变化情况, 提出了网络切换拓扑控制, 该算法利用递归实现自修复, 并且是收敛的. 通过设计相应的分布式算法, 本文将拓扑控制转化为基于局部交互的递归自修复个体控制, 证明了编队自修复个体控制的稳定性. 最后针对编队任务, 通过仿真验证了切换拓扑控制的有效性, 和其他方法比较具有低恢复时间和低功率消耗的优点.     

轨迹跟踪级联机器人编队控制方法

提出一种轨迹跟踪级联机器人编队控制方法. 该方法有效结合距离-角度(??-??) 控制和距离-距离(??-??) 控制方案, 并利用无迹卡尔曼滤波算法对Leader-Follower 级联机器人系统的状态进行估计; 根据状态估计结果设计输入-输出动态反馈控制规律, 使得跟随机器人(Follower) 准确跟踪领航机器人(Leader), 确保编队的稳定性和较快的收敛性, 并达到理想的编队控制效果. 仿真实验验证了所提出方法的可行性.

     

A novel path planning and control framework for passive resistance therapy with a robot manipulator

In this article, we present a paradigm for safe path generation and control for a robotic manipulator such that it provides programmable passive resistance therapy to patients with deficits in the upper extremities. When the patient applies an interaction force at the robot's end-effector, a dynamic path generator time parameterises any therapist-specified contour in the robot's workspace–thus, the robot mimics the dynamics of a passive impedance whose anisotropy vector can be continuously reconfigured. The proposed algorithm is easily implementable because it is robust to uncertainty in the robot dynamics. Moreover, the proposed strategy also guarantees user safety by maintaining the net flow of energy during the human robot interaction from the user towards the manipulator.     

仿人机器人动态步行控制综述

综述了仿人机器人动态步行的研究历史和研究现状。归纳了动态步行的特点,分析了动态步行稳定性判定方法,介绍了基于ZMP的姿态稳定判据和基于庞加莱映射（Poincaré Map）的步态稳定判据。总结了仿人机器人学习适应复杂地面环境步行的方法,概述了动态步行控制实现的典型解决方案,指出了动态步行控制中待解决的问题,并探讨了未来的发展方向。     

A concern-oriented framework for dynamic measurements

Evolving software programs requires that software developers reason quantitatively about the modularity impact of several concerns, which are often scattered over the system. To this respect, concern-oriented software analysis is rising to a dominant position in software development. Hence, measurement techniques play a fundamental role in assessing the concern modularity of a software system. Unfortunately, existing measurements are still fundamentally module-oriented rather than concern-oriented. Moreover, the few available concern-oriented metrics are defined in a non-systematic and shared way and mainly focus on static properties of a concern, even if many properties can only be accurately quantified at run-time. Hence, novel concern-oriented measurements and, in particular, shared and systematic ways to define them are still welcome. This paper poses the basis for a unified framework for concern-driven measurement. The framework provides a basic terminology and criteria for defining novel concern metrics. To evaluate the framework feasibility and effectiveness, we have shown how it can be used to adapt some classic metrics to quantify concerns and in particular to instantiate new dynamic concern metrics from their static counterparts.     

A predictive controller based on dynamic matrix control for a non-minimum phase robot manipulator

In this paper a hybrid control strategy is presented based on Dynamic Matrix Control (DMC) and feedback linearization methods for designing a predictive controller of five bar linkage manipulator as a MIMO system (two inputs and two outputs). Analyzing the internal dynamic of robot shows the open loop system is unstable and non-minimum phase, so in order to apply the predictive controller, special modifications are needed. These modifications on non-minimum phase behavior are performed using feedback linearization procedure based on state space realization. The design objective is to track a desirable set point as well as time varying trajectories as a command references with globally asymptotical stabilization. The proposed controller is applied to nonlinear fully coupled model of the typical five bar linkage manipulator with non-minimum phase behavior. Simulation results show that the proposed controller has good efficiency. The step responses of system with and without feedback linearization process illustrated that the mentioned modification for stabilizing is performed properly. After applying the proposed predictive controller, the joint angle of robot tracks the reference input while another input acts as the disturbance and vice versa.