超高压输电线路巡检机器人越障控制问题的研究

给出了一种超高压输电线路巡检机器人控制系统的设计与实现方法．根据机器人的作业任务,提出了基于传感器信息、约束信息以及动作反馈信息作为输入,产生式系统作为动作输出的越障控制方式．仿真结果表明此方法对于机器人的越障过程是有效的．     

一种输电线路巡检机器人越障规划方法

针对输电线路巡检机器人的局部自主与远程控制方式,提出了一种基于有限状态机的越障规划方法.将巡检机器人的越障运动过程分解成若干离散化的关键状态,建立了运动规划的有限状态机模型.采用一种基于模糊方法的产生式系统用于推理越障模式,并产生运动序列.仿真与现场实验验证了越障规划方法的正确性和有效性,该方法可应用于输电线路巡检机器人运动控制.     

可重构机器人越障运动的规划

提出一种新型的可重构机器人,该机器人在受一个驱动力矩的作用时,在不同约束下表现的输出形式不同. 利用机构这一特点,实现了机器人移动中的自主越障运动．主要针对机器人越障运动中越障高度受导轮和手臂影响的问题,提出一种借助环境同时改变手臂姿态的越障规划方法,有效地提高了越障的高度．通过试验样机验证了规划方法的有效性．     

智能空间下面向动作序列生成的服务机器人指令解析方法

服务机器人在执行家庭任务时存在任务分析困难、环境适应性差、人机交互不友好等问题。为了更加准确地理解用户意图,规划符合当前环境的服务步骤,研究了智能空间下面向序列生成的服务机器人指令智能解析方法,以加强机器人对于家庭环境下服务任务的认知能力。首先,从指令关键词入手,提出了一个基于门控机制的意图识别模型,加强了机器人对用户指令的认知能力。然后,提出了一种以服务策略作为中间状态的序列文本生成机制,用于辅助生成机器人的动作序列。同时,结合机器人与环境的多模态感知,集成了一种基于智能空间本体交互的策略修正机制,以生成最符合当前环境的服务策略。最后,融合了基于领域与问题描述的任务规划模块,为机器人生成可执行的动作序列,从而提升服务任务的执行质量。实验结果表明,本文方法在保证交互友好的同时,能够准确理解复杂的用户指令,并最终生成机器人能执行的可靠动作序列。     

BSCRP网:机器人规划的赋时有色网实现方法

为了解决情景演算无法解决框架问题和生成动作序列效率底的问题,提出了一种基于情景演算推理规则的表示机器人规划的赋时有色网实现方法——BSCRP网(representation based on situation calculus for robot plan),并提出了一种基于双向搜索策略的BSCRP网系统的构造方法。实验结果表明了机器人规划的BSCRP网系统不仅能形式化地描述动作、状态以及动作和状态之间的关系,而且能动态地规划出实现目标的动作序列并计算执行动作序列所需时间。     

多节履带式机器人系统组成和越障性能研究

针对核工业管道内壁检测中环境信息的实时获取需求,研制了结构紧凑的三节履带式越障机器人系统.该系统由控制端和机器人本体组成,以dsPIC芯片群为核心,实现了稳定的无线操控、电机间的协调动作和视频信息的实时采集,并设计了友好的用户操作界面.根据系统的机构特征,探讨了越障过程中姿态调整的稳定性和越障规划等问题.台阶攀爬、沟壑跨越和野外工作等实验结果表明,该机器人系统具备良好的越障性能.     

基于知识库的输电线路巡检机器人的越障控制

介绍了一种高压输电线路巡检机器人越障控制方法。高压输电线路巡检机器人在翻越同一障碍物时重复同一套操作动作,可通过在实验室进行越障过程示教,离线学习形成操作知识库,实际越障时自动调用操作知识库并与在线信号相结合完成自主越障动作。讨论了知识库的一般组成和功能,并分析了激光传感器定位的方法以实现巡检机器人滚动轮与导线“对中”。经过实验验证,该控制方法具有稳定可靠,硬件结构简便,能可靠地完成控制任务,实现自主越障。     

基于结构约束的架空输电线路巡线机器人障碍识别

巡线机器人沿相线行走时必须探测识别各种障碍，并根据障碍类型规划越障行为．针对220 kV架空输电线路的结构特点，利用视觉传感器，设计了基于结构约束的障碍识别算法．算法利用图像的边缘信息，采用改进的基于存在概率图的圆/椭圆检测方法和分层决策机制，以减少自然环境中光线变化和机器人运动对识别质量的影响，满足了巡线机器人的实时越障要求．实验室模拟线路和实际线路实验结果表明，算法能可靠地识别出复杂背景中的防震锤、悬垂线夹和耐张线夹等障碍物．     

基于粒子群模糊的除冰机器人越障规划

由于除冰机器人多在天气恶劣,覆冰较厚的输电线路上工作,现有的基于视觉伺服越障策略存在图像质量差,冰、线区分难等不足。根据模糊逻辑和粒子群优化原理,提出了一种除冰机器人在线越障和路径规划方法。该方法通过模糊规划器实现除冰机器人机械臂的无障跟踪和平稳越障。在此基础上,以机械臂末端经过路径长度和与目标点距离的综合最小为目标,利用粒子群算法对模糊规划器输出角度进行在线优化。仿真结果表明:与传统的模糊越障规划相比,该方法不仅满足除冰机器人实时规划和自主越障的要求,缩短了机械臂经过轨迹的长度,提高了除冰机器人的工作效率和续航能力,为实际工程应用中除冰机器人的能源短缺问题,提供了一种节约使用方案,具有一定的工程应用价值。     

四履带双摆臂机器人越障机理及越障能力

为发挥四履带双摆臂机器人的最佳越障性能,本文从运动学的角度,在固定双履带机器人越障机理的 基础上,分析了四履带双摆臂机器人克服台阶、斜坡、沟道等典型障碍的运动机理及其最大越障能力,重点研究了 四履带双摆臂机器人正向和反向两种攀越台阶方式的运动机理及其最大越障能力．以CUMT-II 型煤矿探测机器人 样机为例,绘制了机器人仰角、摆臂摆角与跨越台阶高度的3 维关系图,以及斜坡坡度与摆臂摆角关系曲线,并求 出了相应的最大越障能力的理论值,与实验室实测数据进行了对比分析．本文推导出机器人的最佳越障性能及对应 的质心和摆臂的位置,可为机器人越障时质心位置的控制提供理论依据．     

基于聚类分析和运动描述语言的扑翼飞行机器人行为规划

为了解决扑翼飞行机器人实时控制过程中操作者工作量大、操作较为复杂的难题,实现扑翼飞行机器人的分布式智能控制,提出了基于聚类分析和运动描述语言的扑翼飞行机器人行为规划方法.利用扑翼飞行机器人飞行数据聚类分析的结果,将机器人运动行为进行合理分类.在保证了运动描述语言的基元关系的同时,合理提取了扑翼飞行机器人的行为特征,并针对扑翼飞行机器人绕杆任务定义了4类运动基元.以扑翼飞行机器人和机载陀螺仪搭建了扑翼飞行机器人实验系统.通过直接控制方法和基于运动描述语言的机器人行为规划方法进行了实物实验和仿真实验,实验结果验证了所提方法的可行性和有效性.     

Method for tuning the motion planning parameters of a mobile robot

This paper presents a method for configuring the motion planning system of an omniwheeled mobile robot with a differential drive. A simulation program that models the horizontal movement of the robot is described. This simulation program is used to select the optimal parameters for the differential drive control algorithm. Then, the motion planning system is tested on a real robot, which is called RB-2, to adjust the parameters selected. This approach allows the control algorithm to be tuned efficiently and effectively, minimizing the number of its test runs on the physical robot.     

机器人运动规划方法的研究

针对路径规划以及碰撞检测这一研究的重点问题,提出了G-空间法、人工势力场法、遗传算法等。序列规划问题一般转化为旅行商问题来求解。在综合现有序列规划和路径规划方法的基础上,提出两种机器人运动规划算法：基于任意路径的运动规划算法和基于直线路径的运动规划算法,思路简单,能对各种机器人工程任务进行运动规划。     

Fuzzy Logic Based Behavior Fusion for Navigation of an Intelligent Mobile Robot

This paper presents a new method for behavior fusion control of a mobile robot in uncertain environments.Using behavior fusion by fuzzy logic,a mobile robot is able to directly execute its motion according to range information about environments,acquired by ultrasonic sensors,without the need for trajectory planning.Based on low-level behavior control,an efficient strategy for integrating high-level global planning for robot motion can be formulated,since,in most applications,some information on environments is prior knowledge.A global planner,therefore,only to generate some subgoal positions rather than exact geometric paths.Because such subgoals can be easily removed from or added into the plannes,this strategy reduces computational time for global planning and is flexible for replanning in dynamic environments.Simulation results demonstrate that the proposed strategy can be applied to robot motion in complex and dynamic environments.     

The VFO-Driven Motion Planning and Feedback Control in Polygonal Worlds for a Unicycle with Bounded Curvature of Motion

Integrated motion planning and control for the purposes of maneuvering mobile robots under state- and input constraints is a problem of vital practical importance in applications of mobile robots such as autonomous transportation. Those constraints arise naturally in practice due to specifics of robot mechanical construction and the presence of obstacles in motion environment. In contrast to approaches focusing on feedback control design under the assumption of given reference motion or motion planning with neglection of subsequent feedback motion execution, we adopt a controller-driven motion planning paradigm, which has recently gained attention of many researchers. It postulates design of motion planning algorithms dedicated to specific feedback control policies, which compute a sequence of feedback control subtasks instead of classically planned open-loop controls or parametric paths. In this spirit, we propose a motion planning algorithm driven by the VFO (Vector Field Orientation) control law for the waypoint-following task. Presented analysis of the VFO control law reveals its beneficial properties, which are subsequently utilized to solve a generally nonlinear and non-convex optimal motion planning problem by formulating it as a mixed-integer linear program (MILP). The solution proposed in this paper yields a waypoint sequence, which is designed for execution by application of the VFO control law to drive a robot to a prescribed final configuration under an input constraint imposed by bounded curvature of robot motion and state constraints resulting from a convex decomposition of task space. Satisfaction of these constraints is guaranteed analytically and exactly, i.e., without utilization of numerical approximations. Moreover, for a given discrete set of possible waypoint orientations, the proposed algorithm computes plans optimal w.r.t. given cost functional, which can be any convex linear combination of quantities such as robot path length, curvature of robot motion, distance to imposed state constraints, etc. Furthermore, the planning algorithm exploits the possibility of both forward or backward movement of the robot to allow maneuvering in demanding environments. Generated waypoint sequences are a compact representation of a motion plan, which can be immediately executed with the VFO controller without any additional post-processing. Validity of the proposed approach has been confirmed by simulation studies and experimental motion execution with a laboratory-scale mobile robot.     

Fuzzy controller for wall-climbing microrobots

This paper presents a fuzzy control system that incorporates sensing, control and planning to improve the performance of the wall-climbing microrobots in unstructured environments. After introduction of the robot system, a task reference method is proposed which is based on a fuzzy multisensor data fusion scheme. The method provides a novel mechanism to efficiently integrate task scheduling, action planning and motion control in a unified framework. A robot gait generation method is described which switches the robot locomotion between different motion modes with the help of a finite state machine driven by sensory information. A fuzzy motion controller is designed to improve control performance and reduce power consumption by the suitable selection of fuzzy sets and inference methods, as well as the definition of corresponding membership functions and control rule bases. A fuzzy logic compensator is developed to compensate the gravitational effects according to different robot configurations and task situations. Experimental results prove the validity of the proposed methods.     

码垛机器人的研究与应用

通过对码垛机器人相关文献进行归纳整理,从结构优化、末端执行机构、运动规划、运动控制、机器人编程、国内应用等六个方面对码垛机器人进行了概述,分别阐述了机器人本体结构优化、运动规划的常见方法、机器人编程的常用手段、机器人控制的常用方法、避障规划的难点、多机器人协同的特殊性、各类型末端执行机构的优缺点,随后针对我国的码垛机器...     

Navigation integration of a mobile robot in dynamic environments

This article presents a design and experimental study of navigation integration of an intelligent mobile robot in dynamic environments. The proposed integration architecture is based on the virtual‐force concept, by which each navigation resource is assumed to exert a virtual force on the robot. The resultant force determines how the robot will move. Reactive behavior and proactive planning can both be handled in a simple and uniform manner using the proposed integration method. A real‐time motion predictor is employed to enable the mobile robot to deal in advance with moving obstacles. A grid map is maintained using on‐line sensory data for global path planning, and a bidirectional algorithm is proposed for planning the shortest path for the robot by using updated grid‐map information. Therefore, the mobile robot has the capacity to both learn and adapt to variations. To implement the whole navigation system efficiently, a blackboard model is used to coordinate the computation on board the vehicle. Simulation and experimental results are presented to verify the proposed design and demonstrate smooth navigation behavior of the intelligent mobile robot in dynamic environments. ©1999 John Wiley & Sons, Inc.