粗轧机前推床同步拉杆断裂的分析与改进

通过对机前推床同步拉杆的受力分析及强度计算，查找出了造成拉杆断裂的原因，并提出了解决拉杆断裂的具体措施。     

Decentralized adaptive coordinated control of multiple robot arms without using a force sensor

This paper presents a distributed adaptive coordinated control method for multiple robot arms grasping a common object. The cases of rigid contact and rolling contact are analyzed. In the proposed controller, the dynamic parameters of both object and robot arms are estimated adaptively. The desired motions of the robot arms are generated by an estimated object reference model. The control method requires only the measurements of the positions and velocities of the object and robot arms, but not the measurements of forces and moments at contact points. The asymptotic convergence of trajectory is proven by the Lyapunov-like Lemma. Experiments involving two robot arms handling a common object are shown.     

模糊环境的表示及机器人轨迹规划

本文利用模糊集理论，提出一种非确定环境的描述方法，并且针对机器人在该类环境中的避障轨迹规划，建立了相应的决策函数和规划策略，最后，给出在ＰＣ－３８６计算机上的仿真试验结果。     

有环境约束时完成一族跟踪任务的力控制

本文为工业机器人提出了一种极点配置控制法，这种控制方法的优点有：一是它的积分作用消除了机器人的微小扰动和稳态误差；二是能任意设置系统的极点，因此能保证闭环系统的稳定性和规定状态变量的暂态响应；三是加入了加速度反馈，抑制了由电枢电感所引起的机械手的振动，最后，给出了ＰＵＭＡ５６２机器人的计算机仿真和实验结果验证了此控制法的有效性。     

用奇异模型描述的受限机器人的学习控制

本文了一类受限机器人的迭代学习控制方案，控制器的设计是基于机器人模型的降阶形式。在存在有界未知干扰的情况下，对末端操纵器受线性、无摩擦约束面的受限机器人。本文给出的控制方案保证了机器人系统的完全运动跟踪，同时保证了力跟踪误差有界的，且界的大小是可调节的。     

管内机器人研究中的几项新技术

介绍了我们研制的管内机器人中应用的具有创新性的三项技术：１．轮式全主动新型行走机构；２．内壁环带视觉装置；３．新型离心喷涂器。     

基于Luv色度坐标图像分割方法的孔洞参数计算

针对成像测井解释中孔洞参数定量计算的准点，提出用基于Luv色度坐标进行图像分割的方法来定量计算孔洞的面积、面孔率等相关参数。采用该方法得到的孔洞结果目标区域完整，可以方便地计算出孔洞面积和面孔率等参数。     

Linear Algebra Considerations for the Multi-Threaded Simulation of Mechanical Systems

A solution method suitable for the multi-threaded simulation ofmechanical systems represented in Cartesian coordinates isproposed and analyzed. In a state-space framework for thesolution of the Differential Algebraic Equations (DAE) ofMultibody Dynamics, the position/velocity stabilization and theacceleration computation are based on iterative solvers applied toequivalent reduced problems. The most in-depth computationalaspect analyzed is the preconditioning, i.e., the direct solutionof the reduced systems. Provided a topology index reduction is first applied to the model, the effort for the direct solution of the reduced systems is shown to be of order O(N _J ), where N _J is the number of joints in the model. The recurring theme of thepaper is the central role that the topology of the mechanicalsystem plays in the overall performance of the numericalsimulation. Based on the topology of the model, parallelcomputational threads can be established to start in the equationformulation and continue through the iterative numericalalgorithms employed for the numerical solution. Task schedulingthese parallel threads is expected to redeem real-time performancefor certain classes of complex applications.     

Minimum-Energy Translational Trajectory Generation for Differential-Driven Wheeled Mobile Robots

Mobile robots can be used in many applications, such as exploration, search and rescue, reconnaissance, security, and cleaning. Mobile robots usually carry batteries as their energy source and their operational time is restricted by the finite energy available from the batteries. Therefore, energy constraints are critical to the service time of mobile robots. This paper investigates the minimum-energy control problem for translational trajectory generation, which minimizes the energy drawn from the batteries. Optimal control theory is used to find the optimal velocity trajectory in analytic form. To demonstrate energy efficiency obtainable, we performed simulations of minimum-energy velocity control and compared the results with loss-minimization control and energy-optimal trapezoidal velocity profiles. Simulation results showed that significant energy savings can be achieved, of up to 9% compared with loss-minimization control and up to 10% compared with energy-optimal trapezoidal velocity profile. We also performed an actual robot experiment using Pioneer 3-AT platform to show the validity of the proposed minimum-energy velocity control. The experimental results revealed that the proposed minimum-energy velocity control can save the battery energy up to 10% compared with loss-minimization control. Categories (3): Robot control, (5): RobotMotion Planning     

Global Level Path Planning for Mobile Robots in Dynamic Environments

This paper presents a self-adapting approach to global level path planning in dynamic environments. The aim of this work is to minimize risk and delays in possible applications of mobile robots (e.g., in industrial processes). We introduce a hybrid system that uses case-based reasoning as well as grid-based maps for decision-making. Maps are used to suggest several alternative paths between specific start and goal point. The casebase stores these solutions and remembers their characteristics. Environment representation and casebase design are discussed. To solve the problem of exploration vs. exploitation, a decision-making strategy is proposed that is based on the irreversibility of decisions. Forgetting strategies are discussed and evaluated in the context of case-based maintenance. The adaptability of the system is evaluated in a domain based on real sensor data with simulated occupancy probabilities. Forgetting strategies and decision-making strategies are evaluated in simulated environments. Experiments show that a robot is able to adapt in dynamic environments and can learn to use paths that are less risky to follow.