“妙手”系统机械结构设计与优化

为了辅助医生更好地完成显微外科手术,开发了一种主从异构的显微外科手术机器人系统——“妙手”系统．“妙手”系统的主手为商业化的Phantom Desktop主手,从手为针对显微外科血管缝合而设计的“妙手”从手．从手包括位置机构和姿态机构．位置机构通过丝传动实现双四连杆机构的运动特性;姿态机构采用三轴交汇于一点的设计思想．通过分析双四连杆机构的运动特性,根据Angeles运动灵活度指标对双四连杆机构进行了优化．结果表明：当双四连杆机构前三级杆等长且I级杆与III级杆垂直时,机构运动灵活度取最大值．     

基于ADAMS的机械四连杆机构运动仿真分析

机械四连杆机构是机械类的典型机构,其设计与运动分析具有很强的理论性和实践性。针对作图法和解析法对该类机构进行运动分析的不足,在基于经典机构学理论的基础上,采用ADAMS(Automatic Dynamic Analysis of Mechanical Systems)动力学仿真方法,可实现对铰链四杆机构的运动特性的直观、高效而准确的计算机辅助分析。然后,采用多体系统动力学理论,通过ADAMS分析了机构的简化方法并进行运动学仿真,对四连杆机构中杆件的传动角、位移、速度及运动轨迹进行了分析。     

Minimization of joint reaction forces of kinematic chains by a multi-objective approach

The paper describes a procedure of simultaneous minimization of joint reaction forces of planar kinematic chains. The best design is sought using the methods of mathematical programming. The optimization model of the kinematic chain is based on a multi-objective approach where the objective functions may be related to the generalized joint forces. The design variables are the geometric parameters of the links. The implementation of the optimization model is illustrated with two examples. The first example considers the minimization of joint reaction forces of an open loop system of a two-arm manipulator. The second example considers optimization of a closed loop system representing a four-bar mechanism being an actual part of a hydraulic support employed in the mining industry.     

Optimal Design of a New Wheeled Mobile Robot Based on a Kinetic Analysis of the Stair Climbing States

In this paper, we propose a new wheeled mobile robot (WMR) with a passive linkage-type locomotive mechanism that allows the WMR to adapt passively to rough terrain and climb up stairs, making it ideal for applications such as building inspection, building security, and military reconnaissance. A simple four-bar linkage mechanism and a limited pin joint are proposed after considering two design needs: adaptability and passivity. To improve the WMR’s ability to climb stairs, we divided the stair-climbing motion into several stages, taking into consideration the status of the points of contact between the driving wheels and the step. For each of the suggested stages, a kinetic analysis was accomplished and validated using the multi-body dynamic analysis software package ADAMS. The object functions are presented for the stages that influence the WMR’s ability to climb stairs. The optimization of the object functions is carried out using the multi-objective optimization method.     

Human like trajectory generation for a biped robot with a four-bar linkage for the knees

The design of a knee joint is a key issue in robotics to improve the locomotion and the performances of the bipedal robots. We study a design for the knee joints of a planar bipedal robot, based on a four-bar linkage. We design walking reference trajectories composed of double support phases, single support phases and impacts. The single support phases are divided in two sub-phases. During the first sub-phase the stance foot has a flat contact with the ground. During the second sub-phase the stance foot rotates on its toes. In the double support phase, both stance feet rotate. This phase is ended by an impact on the ground of the toe of the forward foot, the rear foot taking off. The single support phase is ended by an impact of the heel of the swing foot, the other foot keeping contact with the ground through its toes. A parametric optimization problem is presented for the determination of the parameters corresponding to the optimal cyclic walking gaits. In the optimization process this novel bipedal robot is successively, overactuated (double support with rotation of both stance feet), fully actuated (single support sub-phase with a flat foot contact), and underactuated (single support sub-phase with a rotation of the stance foot). A comparison of the performances with respect to a sthenic criterion is proposed between a biped equipped with four-bar knees and another with revolute joints. Our numerical results show that the performances with a four-bar linkage are bad for the smaller velocities and better for the higher velocities. These numerical results allows us to think that the four-bar linkage could be a good technological way to increase the speed of the future bipedal robots.     

An efficient metamodel-based multi-objective multidisciplinary design optimization framework

This paper presents an efficient metamodel-based multi-objective multidisciplinary design optimization (MDO) architecture for solving multi-objective high fidelity MDO problems. One of the important features of the proposed method is the development of an efficient surrogate model-based multi-objective particle swarm optimization (EMOPSO) algorithm, which is integrated with a computationally efficient metamodel-based MDO architecture. The proposed EMOPSO algorithm is based on sorted Pareto front crowding distance, utilizing star topology. In addition, a constraint-handling mechanism in non-domination appointment and fuzzy logic is also introduced to overcome feasibility complexity and rapid identification of optimum design point on the Pareto front. The proposed algorithm is implemented on a metamodel-based collaborative optimization architecture. The proposed method is evaluated and compared with existing multi-objective optimization algorithms such as multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic algorithm II (NSGA-II), using a number of well-known benchmark problems. One of the important results observed is that the proposed EMOPSO algorithm provides high diversity with fast convergence speed as compared to other algorithms. The proposed method is also applied to a multi-objective collaborative optimization of unmanned aerial vehicle wing based on high fidelity models involving structures and aerodynamics disciplines. The results obtained show that the proposed method provides an effective way of solving multi-objective multidisciplinary design optimization problem using high fidelity models.     

Multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints

Wireless sensor networks have emerged as a promising way to develop high security systems. This paper presents the optimizations of a space-based reconfigurable sensor network under hard constraints by employing an efficient multi-objective evolutionary algorithm (MOEA). First, a system model is proposed for cluster-based space wireless sensor networks. Second, the statement of multi-objective optimization problems is mathematically formulated under hard constraints. Third, the MOEA is used to find multi-criteria solutions in the sense of Pareto optimality. Finally, simulation results are provided to illustrate the effectiveness of applying the MOEA to the multi-objective evolutionary optimizations of a space-based reconfigurable sensor network under hard constraints.     

THROO: a Tracked Hybrid Rover to Overpass Obstacles

In this paper, the design, simulation and experimental tests are presented for THROO: a Tracked Hybrid Rover, which has been developed to Overpass Obstacles. The proposed mobile robot has 3-DOFs and it is capable of straight motion, turning ability and two operations, namely rover-like motion with tracks on flat terrain and walking-like motion with track and legs to overpass obstacles to move on uneven terrain. The leg mechanism is composed of a four-bar linkage, which has been synthesized according to the desired features. In particular, the Burmester problem, which aims at finding the geometric parameters of a four-bar linkage required for a prescribed set of finitely separated poses are solved for the case understudy. Dynamic simulations have been carried out and a prototype has been built. The proposed results show the hybrid rover ability to overpass obstacles, for which size is comparable or greater than the track high.     

A genetic algorithm approach for multi-objective optimization of supply chain networks

Supply chain network (SCN) design is to provide an optimal platform for efficient and effective supply chain management. It is an important and strategic operations management problem in supply chain management, and usually involves multiple and conflicting objectives such as cost, service level, resource utilization, etc. This paper proposes a new solution procedure based on genetic algorithms to find the set of Pareto-optimal solutions for multi-objective SCN design problem. To deal with multi-objective and enable the decision maker for evaluating a greater number of alternative solutions, two different weight approaches are implemented in the proposed solution procedure. An experimental study using actual data from a company, which is a producer of plastic products in Turkey, is carried out into two stages. While the effects of weight approaches on the performance of proposed solution procedure are investigated in the first stage, the proposed solution procedure and simulated annealing are compared according to quality of Pareto-optimal solutions in the second stage.     

Synthesis Optimization of Piezo Driven Four Bar Mechanism Using Genetic Algorithm

Over the past few years, there has been a growing demand to develop efficient precision mechanisms for fine moving applications. Therefore, several piezoelectric driven mechanisms have been proposed for such applications. In this work an optimal synthesis of a four-bar mechanism with three PEAs is proposed. Two evolutionary multi-objective Genetic Algorithms (GAs) are formulated and applied; A Genetic Algorithm Synthesis method (GAS) is first used to obtain a synthesis solution for the mechanism regardless of power consumption. Then another Genetic Algorithm Minimum Power Synthesis method (GAMPS) is used to obtain the synthesis solution of minimum power consumption. For that purpose, the study performs simulation investigation of the aforementioned algorithms for each point along sinusoidal and kidney shaped paths of motion. Results show capability of both methods in obtaining a synthesis solution. However, GAMPS outperformed GAS in terms of driving power consumption as it is minimized by 99% ratio.     

水稻气力抛秧原理与方案研究

在对国内外水稻钵苗移植机械综合分析的基础上提出了气力抛秧的原理，并进行了方案设计和研究。结果表明，气力抛秧原理是可行的，能有效地解决目前机械抛秧存在的问题。     

Research on quality performance conceptual design based on SPEA2+

In order to solve the multi-objective performance optimal problems, SPEA2+ is used to realize the performance design of injection molding machine. The optimization objectives are constructed to maximize mould control power, maximize injection quantity and minimize injection power. The mathematical model is found to optimize the problem. A solution is extracted to eliminate the imprecise nature of preference through the Pareto optimal set based on fuzzy set theory. Compared with NSGA-II and SPEA2, SPEA2+ could acquire the Pareto front with better distribution and smaller distance with the optimum solutions. Finally, the case illustration of HTG1000X3Y injection molding machine is taken as an example to demonstrate that such method is effective and practical. Effective references could be provided to decision makers for objectives tradeoff at the performance conceptual design stage of injection molding machine.     

Dynamic allocation of reconfigurable resources ina two-stage Tandem queueing system with reliability considerations

Consider a two-stage tandem queueing system, with dedicated machines in each stage. Additional reconfigurable resources can be assigned to one of these two stations without setup cost and time. In a clearing system (without external arrivals) both with and without machine failures, we show the existence of an optimal monotone policy. Moreover, when all of the machines are reliable, the switching curve defined by this policy has slope greater than or equal to -1. This continues to hold true when the holding cost rate is higher at the first stage and machine failures are considered.     

单自由度转动式对心机械夹持器

近年来许多学者提出了各种新型的机械夹持器,对心夹持器就是其中的一种.现有的对心机械夹持器的主要缺点是结构复杂,设计麻烦,加工困难,夹持范围小.本文提出一种新的结构简单,制造容易,使用方便,夹持范围大,对心夹持精度高,能对心夹持各种圆柱体的转动式机械夹持器.这种夹持器是根据同心圆在同一圆心角下的不同圆上的弦相互平行的几何关系和平行四杆机械的运动特点设计的.夹持器的每侧是由摇杆滑块机构外接平行四杆机构组成的.     

柔性机器人协调操作闭链负载机构的一般模型

本文利用闭链刚性负载内部运动参数之间的微分关系,在单柔性机器人有限元动力 学模型基础上,建立了系统的运动学和动力学协调约束条件,首次导出了基于负载运动任务 参数的柔性机器人协调操作闭链刚性负载的动力学方程,并给出了两3R柔性机器人协调操作 刚性四杆机构的仿真算例．     

Hybrid multi-objective shape design optimization using Taguchi’s method and genetic algorithm

This research is based on a new hybrid approach, which deals with the improvement of shape optimization process. The objective is to contribute to the development of more efficient shape optimization approaches in an integrated optimal topology and shape optimization area with the help of genetic algorithms and robustness issues. An improved genetic algorithm is introduced to solve multi-objective shape design optimization problems. The specific issue of this research is to overcome the limitations caused by larger population of solutions in the pure multi-objective genetic algorithm. The combination of genetic algorithm with robust parameter design through a smaller population of individuals results in a solution that leads to better parameter values for design optimization problems. The effectiveness of the proposed hybrid approach is illustrated and evaluated with test problems taken from literature. It is also shown that the proposed approach can be used as first stage in other multi-objective genetic algorithms to enhance the performance of genetic algorithms. Finally, the shape optimization of a vehicle component is presented to illustrate how the present approach can be applied for solving multi-objective shape design optimization problems.     

Characterization of reconfigurable Stewart platform for contour generation

The limited treatment available for Stewart platform characteristics leads to the lack of an efficient methodology for determining the optimum geometry for different tasks. In this paper, an effort is made to characterize the parameters for developing a reconfigurable Stewart platform for the contour generation application. A solution is provided through the formulation of dimensionless parameters in combination with a study on the generic parameters like configuration. The variable geometry approach for the reconfiguration of Stewart platform has been adopted for four different platforms, and a generic approach is formulated after studying different parameters. A stiffness model developed for contour generation application is used in tandem with this generic approach to identify the trajectory with maximum stiffness for complex contours. The proposed methodology provides a holistic approach to develop a complete set of design tool to choose the optimum geometry for any new reconfigurable Stewart platform to be developed.     

Robust design optimization with bivariate quality characteristics

In robust design optimization, if Taguchi quality loss function is employed, its expectation is minimized. When multiple quality characteristics exist, their covariances appear in the expectation and usually require numerical integrations. In this work, we propose an analytical robust design approach without numerical integrations to problems with bivariate quality characteristics. The quality characteristics are assumed to be functions of independent normal random variables with small uncertainties. Because the uncertainties are small, the functions are linearized with good accuracy. Analytical equations are then derived for the expected quality loss. The approach is efficient because no numerical integrations are needed. It is applied to the robust synthesis of a four-bar linkage.     

Pareto optimum design of an adaptive robust backstepping controller for an unmanned aerial vehicle

This research develops an adaptive robust backstepping (AR-backstepping) controller for stabilization of an unmanned aerial vehicle (UAV) having strong coupling and highly nonlinear dynamics. At first, the backstepping control method as the basic stabilizer is utilized to determine the control efforts of the considered UAV. Next, an adaptive-robust mechanism subject to gradient decent methods and sliding surfaces is implemented to regulate the control gains. In fact, this mechanism determines the speed of changes of the gain values of the backstepping controller to make better responses in the presence of disturbances and uncertainties. Then, the optimum values of the design parameters related to the adaptive-robust mechanism are selected by using a multi-objective ant-lion optimization (MOALO) algorithm to simultaneously minimize the total error and control efforts. Finally, the results for a UAV developed in the Sirjan University of Technology, Sirjan, Iran, are given to confirm the effectiveness, robustness, and advantages of the designed AR-backstepping controller.