Multiple tasks manipulation for a robotic manipulator

Robotic manipulators can execute multiple tasks precisely at the same time and, thus, the task-priority scheme plays an important role in implementing multiple tasks. Until now, several algorithms for task-priority have been used in solving the inverse kinematics for redundant manipulators. In this paper, through the comparative study of existing algorithms, we will propose a new method for task-priority manipulation in terms of two important criteria—algorithmic singularity and task error. This manipulation scheme will be applied to a planar three-link manipulator to demonstrate its effectiveness.     

Comparison of Two Sequencing Techniques to Perform a Vision-Based Navigation Task in a Cluttered Environment

We address the problem of multi-sensor-based navigation in a cluttered environment for a non-holonomic robot. To perform such a successful and safe navigation, three controllers realizing, respectively, nominal vision-based navigation, obstacle bypassing and occlusion avoidance have been designed using the task function approach. Then it suffices to sequence them to realize the complete mission. To guarantee the control continuity when switching between two successive controllers, two sequencing approaches have been used and compared. Simulation results validate our work.     

Real-time zero moment point compensation method using null motion for mobile manipulators

This paper presents a method to deal with the dynamic stability for a mobile manipulator. Although the system has static stability, manipulation on the moving base or mobile locomotion with a manipulator may cause the system to turn over due to dynamics, so the controller of a mobile manipulator is carefully designed. In this paper, to define the dynamic stability for a mobile manipulator, the zero moment point (ZMP) is used. ZMP is a very useful measure of the dynamic stability. However, if the degrees of freedom of the system are large, the calculation algorithm is very complicated. So, to simplify the calculation algorithm, we define ZMP using the iterative Newton–Euler formulation. Next, a unified approach for the two subsystems, i.e., mobile and manipulator, is formulated using a redundant scheme. To conserve the dynamic stability of the system in real-time, we define the performance index for the redundant system using ZMP. Then, the redundancy resolution problem for optimizing the proposed performance index is solved using the null motion optimization. Finally, the performance of the proposed method is demonstrated by simulation.     

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.     

A real-time impedance-based singularity and joint-limits avoidance approach for manual guidance of industrial robots

This paper studies real-time manual guidance considering singularity and joint-limits avoidance using impedance control in an industrial scenario. The operator is responsible for keeping the end-effector (EE) away from the robot’s singularity and joint-limits. The proposed approach detects the singularity and joint-limits in real-time. Then, virtual stiffness and damping are added to target stiffness and damping as the robot is getting close to the singularity or joint-limit. A criterion is presented for detection of singularity by combining manipulability ellipsoid and condition number. Also a new joint to Cartesian space transformation is formulated in order to convert joint stiffness and damping to Cartesian stiffness and damping for joint-limits avoidance method. The presented approach is applied on a SCARA robot. An experiment is performed in this paper to investigate singularity and joint-limits avoidance separately as well as together. Increase in stiffness and damping warn the operator of the possibility of singularity or joint-limits allowing the operator to changes the EE path. The proposed approach, eliminates the need for a robotics expert by allowing any operator with no knowledge about robot singularity and joint-limits to interact and teach the robot in a safe, real-time and time-saving manner.     

机器人机械手的离散时间学习控制*

本文为机器人机械手提出了一种基于离散时间的重复学习控制法，这种学习控制法利用机器人动力学模型的部分知识，从它的特性和实用观点看，这种控制法比现有的其它学习控制法更有吸引力，本文还给出了学习控制法的收敛性证明和计算机仿真结果。     

CAD-based generation of collision-free paths for robotic manipulators

The use of a CAD system can improve the overall efficiency of automated factories. This paper describes the utilization of a CAD system devoted to the off-line generation of collision-free paths for robotic manipulators. This tool is first applied in the case of a robotic manipulator in a moderately cluttered environment, next it is utilized it for planning collision-free paths for two robotic manipulators sharing a common workspace. The implemented off-line programming system is written in C, in X/Windows environment. In this way portability is effectively achieved. Simulation results show the effectiveness of the proposed approach.     

Fuzzy-neuro position/force control for robotic manipulators with uncertainties

The performance of a controller for robot force tracking is affected by the uncertainties in both the robot dynamic model and the environmental stiffness. This paper aims to improve the controller’s robustness by applying the neural network to compensate for the uncertainties of the robot model at the input trajectory level rather than at the joint torque level. A self-adaptive fuzzy controller is introduced for robotic manipulator position/force control. Simulation results based on a two-degrees of freedom robot show that highly robust position/force tracking can be achieved, despite the existence of large uncertainties in the robot model.     

Dynamic obstacle avoidance for real-time character animation

This paper proposes a novel method to control virtual characters in dynamic environments. A virtual character is animated by a locomotion and jumping engine, enabling production of continuous parameterized motions. At any time during runtime, flat obstacles (e.g. a puddle of water) can be created and placed in front of a character. The method first decides whether the character is able to get around or jump over the obstacle. Then the motion parameters are accordingly modified. The transition from locomotion to jump is performed with an improved motion blending technique. While traditional blending approaches let the user choose the transition time and duration manually, our approach automatically controls transitions between motion patterns whose parameters are not known in advance. In addition, according to the animation context, blending operations are executed during a precise period of time to preserve specific physical properties. This ensures coherent movements over the parameter space of the original input motions. The initial locomotion type and speed are smoothly varied with respect to the required jump type and length. This variation is carefully computed in order to place the take-off foot as close to the created obstacle as possible. Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

基于力/力矩信息的面向位控机器人的阻抗控制

为了克服末端接触点距离力传感器中心较远时,力传感器测量实际接触力的局限性,分析实际作用力与测量力/力矩值之间的关系,利用力传感器信息或力矩信息得到位置控制方向和力控制方向.根据位控与力控方向对机器人末端进行参考轨迹规划,在阻抗控制律中应用参考比例因子调节参考轨迹.基于力误差信息通过模糊推理调节参考比例因子的大小,使生成的参考轨迹适应未知表面的变化.实验结果表明,所提出的控制方法能实现未知工件表面的恒力跟踪.     

A new method for actuating parallel manipulators

This paper presents a new technique of actuating a parallel platform manipulator using shape memory alloy (SMA). This is a type of smart materials that can attain a high strength-to-weight ratio, which makes them ideal for miniature application. The work is mainly to develop a new SMA actuator and then incorporating the actuator in building the parallel manipulator prototype. The SMA used in this study is a commercial NiTi wire. The SMA wire provides an actuating force that produces a large bending and end displacement. A 3-UPU (universal–prismatic–universal) parallel manipulator using linear SMA actuators was developed. The manipulator consists of a fixed platform, a moving platform and three SMA actuators. The manipulator workspace was specified based on the restrictions due to actuator strokes and joint angle limits. System identification techniques were used to model both heating and cooling processes. An ON/OFF control was performed and the results showed closeness in simulation and experimental results. This study showed that shape memory alloy actuated beam can successfully be used to provide linear displacement. The built prototype indicates the feasibility of using SMA actuators in parallel manipulators.     

用于避障研究的微型仿生机器鱼3维仿真系统

基于VC++6.0开发环境和OpenGL（open graphics library）国际图形标准,在Windows系统下开发了微型仿生机器鱼3维仿真系统。该系统可以降低用实体机器鱼进行机器鱼避障能力研究的成本和减少在研究过程中对实体机器鱼造成的损害。采用多边形建模的方法构建了虚拟微型仿生机器鱼模型,模拟了鱼类尾鳍的摆动。提出了一种模拟红外传感器探测障碍物的虚拟射线方法。并采用实时模糊决策算法设计了基于多传感器信息的复合模糊控制器,决策微型仿生机器鱼的避障行为。仿真实验表明,复合模糊控制器实时性好、效率高;无论是单个任意形状的障碍物还是多个连续障碍物,复合模糊控制器都能有效地引导仿生机器鱼避开障碍物,到达目标点。微型仿生机器鱼3维仿真系统为研究仿生机器鱼的自主避障能力提供了可靠、逼真、便利的平台。     

Automatic clustering method for real-time construction simulation

Simulation of construction activities in a virtual environment can prevent constructability problems and increase efficiency and safety at the physical construction site. The computation for collision checks creates a bottleneck during these simulations. A typical construction simulation requires collision checks to be performed between all pairs among thousands or even millions of objects, and each of these checks must be completed within 1/10th or even 1/20th of a second to provide a smooth real-time simulation. Therefore, the reduction of computational cost is paramount. An effective and commonly used method is to cluster the objects into groups and use a larger surrounding boundary shape in place of the individual objects. This significantly reduces the computational effort required. However, clustering objects manually is usually time consuming and is difficult especially for large scenarios. In this paper, we develop an automatic clustering method, called the Propagation Clustering Method (PCM). PCM employs k-means clustering to iteratively cluster objects into multiple groups. A quality index is defined to evaluate the clustering results. Once the clustering results satisfy the predefined quality requirement, the group of objects is replaced by a rectangular box using the axis-aligned bounding box (AABB) algorithm. The rectangular box is then stored in a tree structure. To verify the feasibility of the proposed PCM, we defined three testing scenarios: a site with scattered objects, such as a small plant construction; a common construction site; and a large site with both common structures and scattered objects. Experimental results show that PCM is effective for automatically grouping objects in virtual construction scenarios. It can significantly reduce the effort required to prepare a construction simulation.     

A scalable method for testing real-time systems

Real-time systems (RTSs) are used in different domains such as telephone switching systems, air traffic control systems and patient monitoring systems. The behavior of RTSs is time-sensitive; that is, RTSs interact with their environment with input and output events under time constraints. The violation of such time constraints is the main cause of the misbehavior of RTSs, and may result in severe damage to human lives and the environment [Mandrioli, D., Morasca, S., & Morzenti, A. 1995. ACM Transactions on Computer Systems, 13(4), 365–398]. To prevent failures in RTSs, we must verify that the implementation of an RTS is correct before its deployment. Testing is one of the formal techniques that can be used to achieve this goal. It consists of three main phases: test generation, test execution, and test results analysis. This paper presents a test case generation method for RTSs modeled as Timed Input Output Automata (TIOA). The approach is made in two steps. First, the TIOA describing the system being tested is sampled to construct a subautomaton, which is easily testable (i.e., easy to generate test cases from it). Then, the resulting subautomaton is traversed to generate test cases. Our method is scalable in the sense that it generates a small number of test cases even when the specifications are significant. Moreover, the test cases derived by our method are executable (i.e., they can be run on any error-free implementation of the system being tested).

基于人工势场法的多智能体编队避障方法

编队避障问题是多智能体编队研究的关键问题之一。针对动态环境中多智能体编队避障问题,提出了一种基于人工势场法（APF）与布谷鸟搜索算法（CS）相结合的编队避障方法。首先,在动态队形变换策略的异构模式下,利用APF为多智能体编队中每个智能体规划避障;然后,针对APF在引力增量系数和斥力增量系数设置的局限性,利用CS中的莱维飞行机制思想,来随机搜索得到适应环境的增量系数。Matlab仿真实验结果表明,所提方法能够有效地解决复杂环境下多智能体编队避障问题,使用效率函数对实验数据进行评价及分析,验证了所优化方法的合理性和有效性。     

Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork

Multi-agent domains consisting of teams of agents that need to collaborate in an adversarial environment offer challenging research opportunities. In this article, we introduce periodic team synchronization (PTS) domains as time-critical environments in which agents act autonomously with low communication, but in which they can periodically synchronize in a full-communication setting. The two main contributions of this article are a flexible team agent structure and a method for inter-agent communication. First, the team agent structure allows agents to capture and reason about team agreements. We achieve collaboration between agents through the introduction of formations. A formation decomposes the task space defining a set of roles. Homogeneous agents can flexibly switch roles within formations, and agents can change formations dynamically, according to pre-defined triggers to be evaluated at run-time. This flexibility increases the performance of the overall team. Our teamwork structure further includes pre-planning for frequently occurring situations. Second, the communication method is designed for use during the low-communication periods in PTS domains. It overcomes the obstacles to inter-agent communication in multi-agent environments with unreliable, single-channel, high-cost, low-bandwidth communication. We fully implemented both the flexible teamwork structure and the communication method in the domain of simulated robotic soccer, and conducted controlled empirical experiments to verify their effectiveness. In addition, our simulator team made it to the semi-finals of the RoboCup-97 competition, in which 29 teams participated. It achieved a total score of 67–9 over six different games, and successfully demonstrated its flexible teamwork structure and inter-agent communication.     

具有奇异位置的多体系统动力学方程的改进算法

多体系统进行数值仿真时,很多选择了微分代数混合方程作为多体系统动力学数学模型.本文在现有的约束稳定化理论基础上,提出了针对具有奇异位置的多体系统动力学方程的改进算法.算法通过修正速度违约和控制稳定项,讨论了具有奇异位置的微分代数混合方程的数值仿真问题并给出了稳定项中相关系数的建议值,从而有效克服了求解混合方程时因为构型奇异给计算造成的困难.算例分别采用改进算法与ADAMS软件进行仿真,计算结果的比较表明了改进算法的有效性.本文给出的基于能量守恒的能量差曲线也证明了改进算法的有效性.     

面向实时交通视觉监控的综合动态背景更新方法

为了从复杂的交通场景中获取高质量的背景图像，提出了一种综合的动态背景更新方法。同时使用了帧差信息和提取的高层对象状态信息对混合高斯背景模型进行选择性更新，克服了因较长时间停车对背景的影响，并能及时消除由于背景物体移出造成的鬼影。对实时交通视频的处理效果表明，该方法兼具良好的自适应性与鲁棒性。     

一种星载InSAR高精度快速DEM重建方法

面对全球干涉测量的海量实测数据,在保持精度的情况下,如何提高处理速度是星载干涉合成孔径雷达(interferometric synthetic aperture radar,InSAR)数据处理必须考虑的重要问题.数字高程模型(digital elevation model,DEM)重建是InSAR数据处理中较为耗时的一个关键环节.针对星载InSAR处理中DEM快速重建的难题,从DEM重建原理出发,分析揭示了干涉相位与目标点三维坐标映射关系的两个基本特性,一是目标点的三维坐标与干涉相位的关系可以分别用多项式来进行拟合,二是SAR图像上相近像素各自对应的多项式变化不大,并从理论上对特性的成立进行了论证.基于此,提出了一种快速DEM重建方法,给出了快速算法的详细步骤及关键参数的取值方法.最后,利用德国最先进的在轨雷达卫星TerraSAR-X获取的重复轨道干涉数据进行快速DEM重建,处理结果表明在重建精度损失较小的情况下,显著提高了重建速度,验证了该方法的高效性和正确性.     

基于两阶段多目标模糊决策的乒乓球机器人击球点选择

对乒乓球机器人而言,回球时根据来球状态选择合适的击球点,可以降低回球难度,提高回球成功率.本文提出了一种利用多目标模糊决策确定击球点的方法.首先,根据机器人最优运动区间和来球速度确定搜索区域.然后,定义搜索区域内的相关轨迹点为决策论域.在此决策论域内,根据回球目标参数分别计算期望出球速度,并根据球拍参数定义了3个能量函数,分别代表乒乓球被击打前后的能量和动量变化.以此能量函数为指标函数决策得到优化的击球点.最后,在不同的实验情况下,对比了本文算法与固定高度平面算法,验证了本文算法的有效性.