可移动机器人的运动学模型与控制原理

本文首先对可移动机器人的运动学进行了分析，建立了运动学模型与控制结构图，然后采用时域分析法对此系统进行了校正，最后通过对此系统的仿真与时测实验，对各校正环节的参数进行了整定。     

使用遗传算法的迷宫学习

本文试用遗传计算及决策制定方法来实现机器人有认识迷宫意向的能力，这里“意向”是指遵循对迷宫特有的路径规则所出的决定，令机器人在两个相对的迷宫中行走学习，一个迷宫路径是基于同样的意向，另一个则基于不同的意向，研究结果确认了已达成的意向学习。     

遥操作工程机器人系统临场感技术研究-6自由度临场运动感觉反馈技术的研究进展

 研究开发出一种遥操作工程机器人系统，可以应用于诸如火灾现场的修复作业等广阔的领域．该系统由伺服控制的工程机器人、2根从远处操纵工程机器人的操纵杆、视频系统和6自由度运动模拟器组成．操作者坐于座椅上，座椅固定于运动模拟器的上方． 该系统需要解决的一个关键问题是如何使操纵者高质量地获得工作现场的临场运动感觉． 提出了一种6自由度临场运动感觉反馈方法，其信号源来自工程机器人上安装的6个加速度传感器． 该方法的有效性已为实验所证明，即应用6自由度运动模拟器不但可以高质量地模拟工程机器人单个自由度的运动：滚动、俯仰、转动以及前后、左右、上下的平移，而且可以高质量地模拟工程机器人的各种复合运动．     

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。     

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.     

机械臂的动态混合控制

本文研究当机械臂的终端受有约束时的控制问题,其中心内容是给出“任务规范投影算子”的概念,利用它首先将机械臂的动态方程解耦为两组方程,它们分别描述了运动与约束力,在此基础上给出了机械臂的控制律,使闭环系统跟踪期望的速度与约束力。