双臂机器人无碰撞运动规划

针对双臂机器人任务操作中的非结构化环境特点 ,本文对双臂机器人无碰撞运动规划问题作了深入的研究 ,将 C空间法成功地应用于双臂机器人的无碰撞运动规划 ,通过建立时变 C空间 ,提出了从臂无碰撞状态数据库(CSDB)概念。在本算法中 ,双臂机器人无碰撞运动路径可以通过对从臂无碰撞状态数据库的搜索获得 ,运用该算法可以在时变 C空间中得到一条最优的无碰撞运动路径 ,本算法已经在双臂 SCARATES型机器人上通过试验论证 ,证明算法可行 ,效率较高     

Collision-free motion planning of dual-arm robot

０ＩＮＴＲＯＤＵＣＴＩＯＮＤｕａｌａｒｍｒｏｂｏｔｉｓａｎｅｗｔｙｐｅｏｆｒｏｂｏｔｗｈｉｃｈｈａｓｂｅｅｎｄｅｖｅｌｏｐｅｄｉｎｒｅｃｅｎｔｔｗｏｙｅａｒｓ．Ｔｈｅｕｓｅｏｆｔｈｉｓｔｙｐｅｏｆｒｏｂｏｔｃａｎｇｒｅａｔｌｙｉｍｐｒｏｖｅｒｏｂｏ...     

一种新的编码方法解决路径规划问题

提出了一种在极坐标环境下应用遗传算法求解机器人路径规划问题的方法.该方法采用简洁有效的路径染色体编码方法和快速的个体适应度计算方法,并对生成的初始路径点集进行提炼处理,以剔除其中含有的不必要拐点;仿真结果表明该方法可以解决大范围、多障碍环境的机器人路径规划问题.     

基于启发式的快速扩展随机树路径规划算法

针对基于随机采样的路径规划缺乏确定性的问题,提出一种具有启发式的多自由度机器人路径规划算法.该算法在快速扩展随机树算法的基础上,引入了启发式估价函数,使扩展随机树有利于朝目标点方向进行生长.仿真结果表明,提高了复杂环境下机器人路径规划的效率,保证了规划的路径接近于最短路径,对同一任务的规划具有一定的可重复性.     

自重构模块化机器人的运动空间及自变形算法

设计一种新颖的同构式模块化自重构机器人系统,该自重构机器人系统的基本模块由1个中心体和6个旋转面组成.根据模块的运动特征及棋盘规则的约束,以Oxy平面为例,分4种情况,研究并归纳出该自重构模块化机器人系统的可能运动空间.利用当前构型重心和目标构型重心之间距离的函数作为驱动模块运动的启发信息,根据每个模块自身的可能运动空间,并结合模块对目标位置的逐步填充方式共同完成系统的自重构运动规划.为了能快速完成该类自重构模块化机器人的自变形任务,定义模块的优先运动系数,规定模块的填充原则,将逐步填充式自变形算法进行一定优化,得出该类自重构模块化机器人系统的自变形方法.最后给出一个16模块自重构机器人系统的变形仿真实例,证明上述方法的可行性.     

极坐标系下基于遗传算法的路径规划方法

提出了一种在极坐标环境下应用遗传算法求解机器人路径规划问题的方法 ,该方法采用简洁有效的路径染色体编码方法和快速的个体适应度计算方法 ,并对生成的初始路径点集进行提炼处理 ,以剔除其中含有的不必要拐点 ;仿真结果表明该方法可以解决大范围、多障碍环境的机器人路径规划问题     

基于遗传模拟退火算法的弧焊机器人系统协调路径规划

深入地研究了弧焊机器人系统的协调路径规划。从全局的角度用5元组序列描述了焊接路径。设计了评价 焊接路径目标函数:焊接位置函数、焊缝成形质量函数、关节位置函数和运动平稳性函数。以线性加权法为求解 多目标规划的基本思想,把遗传模拟退火算法用于弧焊机器人与变位机协调路径规划,取得了很好的效果。协调 路径规划精确地保证焊缝的最佳焊接位置与最佳的焊枪姿态,并能找到柔顺的焊接路径,提高了机器人焊接的质 量和效率。     

机器人室内路径规划算法的实用性研究

机器人研究领域中的一个关键分支即路径规划技术,本课题在机器人P3-DX实验平台的基础上,通过栅格化建模对室内的环境实现分块。4种路径规划〖CD2〗回字形路径规划、迂回式路径规划、启发式路径规划与包围式路径规划的可行性已经得到验证,为验证4种路径规划的实用性,在真实环境中将这4种路径规划算法进行了实验研究,通过软件将机器人行走后返回的数据绘制出相应的路线图,同时,根据各路径规划算法的路线图的不同重复率与覆盖率,找出效率较高的路径规划算法。     

一种气门电镦成型机器人轨迹规划与仿真研究

运用D-H法建立气门电镦成型机器人数学模型,并进行运动学正逆解。根据实际现场对机器人运动路径要求,规划其运动路径,现场通过示教获取机器人运动关键点,并在关节空间进行B样条曲线轨迹规划研究,获取关节空间轨迹运动函数表达式,并利用Matlab工具对规划轨迹进行仿真模拟。结果表明利用该方法能生成一条关节位移、速度、加速度都连续的平滑运动轨迹,以保证机器人工作时按规定的路径平稳地运行,且能顺利避开障碍物,满足设计和使用要求。     

变电站轮式巡检机器人机械臂避障路径规划方法

变电站工作环境特殊且复杂,为保证巡检机器人在执行巡检任务的同时,能更好、更安全地进行作业,提出面向轮式巡检机器人的机械臂避障路径规划方法。利用八叉树结构建模技术,架构巡检机器人工作环境的三维模型与环境更新模型。确定机械臂与环境关系,建立机械臂运动学模型,根据末端执行器位姿的已知与未知情况,完成运动学模型的正解与反解计算。基于关节位姿的三维坐标,设定机械臂连杆不碰撞障碍物为必要条件,依据六次多项函数式解得的关节角速度与角加速度连续轨迹,通过更改非固定参数值,调整机械臂的移动轨迹,最后,利用贝塞尔曲线平滑处理路径。仿真试验结果表明,所提方法路径精度更优越,避障效果更理想,符合变电站巡检的实时性需求。     

移动机器人全覆盖路径规划算法研究

针对静态未知环境下移动机器人全覆盖路径规划问题,提出了一种改进优先级蚁群算法。该算法首先通过机器人本体上的传感器构建基于动态栅格法的工作环境;综合考虑栅格属性、机器人转向、邻域栅格距离和未覆盖区域面积大小的基础上构造优先级启发规则,然后利用该规则进行路径全覆盖工作。针对机器人工作过程中出现的死锁问题,文章提出采用蚁群算法寻找逃离死区的最优路径,从而保证机器人实现路径全覆盖,并使覆盖路径的重复率尽可能小。仿真实验中,通过与传统算法比较,验证所提算法能在保证面积覆盖率为100%的同时,降低了死锁次数和轨迹重复率,从而提高了机器人工作效率。     

基于SimMechanics的轮式移动机器人轨迹仿真

轮式移动机器人因具有非完整约束的不可积分性,其控制与规划等问题变得相当困难与复杂.利用SimMechanics工具,通过对轮式移动机器人平面运动的分析,建立了轮式移动机器人的运动学模型,并对其运动进行了多次的仿真,得到其运动轨迹,通过与理论轨迹的对比,验证了运动模型的正确性.该模型还提供了参数输入的接口,能够根据实际的...     

Navigation planning for mobile robotic devices in modular warehouses

This paper deals with the problem of navigation and planning of an automated warehouse equipped with mobile robotic devices. A generalised layout of the warehouse is considered here, which is a modular construction type. The path planning algorithm (optimises the path for the shortest distance to the goal) and the collision avoidance strategy for a multiple robot environment are developed based on velocity and distance bounds. The landmarks are assumed to supply all pertiment information regarding the module identification and the movement directions, while the sensors are assumed to be capable of maintaining the robot in its correct track and understand the knowledge contained in the landmarks. The path planning and collision avoidance algorithms are programmed and simulated for a multiple robot environment in a construction site warehouse.     

Robot trajectory optimisation with dynamic constraints

Objects located within a robot arm workspace fragment this space, since a path obstructed by an object is non-viable. Point-to-point motion of a robot arm in such a fragmented workspace has to be carefully planned in order to avoid collision. The problem of planning the trajectory of the robot arm can be represented as a constrained optimisation problem from which an optimal time can be deduced. The solution of the optimisation problem for an optimal continuous trajectory is complex and costly. However, a motion strategy, whereby the robot arm path is formed of single linear segments, renders the optimisation problem solvable and produces a sub-optimal but practical trajectory. This paper describes a motion strategy that is based on the concept of defining via intermediate and control points which the robot arm has to pass by along its path, and takes into consideration the torque limitation of the different axis drives. Joint motion planning is based on a function of time approximated by a sequence of polynomials with boundary conditions that would result in continuous motion at the via points. Motion between each two points is divided into two transition zones and a constant speed zone in between. A result is obtained by selecting polynomial coefficients that would minimise, subject to the constraints of the robot dynamics, the time required to accelerate and decelerate the joint to the appropriate speeds at the boundary of these zones. The joint is allowed to move at the maximum speed for the remainder of the time.     

Autonomous mobile robot navigation system designed in dynamic environment based on transferable belief model

This paper investigates the possibility of using transferable belief model (TBM) as a promising alternative for the problem of path planning of nonholonomic mobile robot equipped with ultrasonic sensors in an unknown dynamic environment, where the workspace is cluttered with static obstacles and moving obstacles. The concept of the transferable belief model is introduced and used to design a fusion of ultrasonic sensor data. A new strategy for path planning of mobile robot is proposed based on transferable belief model. The robot’s path is controlled using proposed navigation strategy that depends on navigation parameters which is modified by TBM pignistic belief value. These parameters are tuned in real time to adjust the path of the robot. A major advantage of the proposed method is that, with detection of the robot’s trapped state by ultrasonic sensor, the navigation law can determine which obstacle is dynamic or static without any previous knowledge, and then select the relevant obstacles for corresponding robot avoidance motion. Simulation is used to illustrate collision detection and path planning.     

移动机器人在线实时路径规划

研究了不确定环境下移动机器人的路径规划问题。采用全局规划和局部规划相结合的方法，提出了一种基于极坐标空间，以期望方向角为优化性能指标的在线实日寸路径规划方法。该法利用机器人的传感器系统，实时探测局部环境信息，在每次的局部规划窗口，确定机器人的期望方向角，以机器人的实际运动方向角与期望方向角之间的差异来驱动机器人避开障碍物和朝向目标点运动。该法不仅简单灵活，而且克服了全局规划和局部规划的缺陷。仿真实验表明其有效可行性、实时性、优化性、精度高、稳定性好。     

Computational path planner for product assembly in complex environments

Assembly path planning is a crucial problem in assembly related design and manufacturing processes. Sampling based motion planning algorithms are used for computational assembly path planning. However, the performance of such algorithms may degrade much in environments with complex product structure, narrow passages or other challenging scenarios. A computational path planner for automatic assembly path planning in complex 3D environments is presented. The global planning process is divided into three phases based on the environment and specific algorithms are proposed and utilized in each phase to solve the challenging issues. A novel ray test based stochastic collision detection method is proposed to evaluate the intersection between two polyhedral objects. This method avoids fake collisions in conventional methods and degrades the geometric constraint when a part has to be removed with surface contact with other parts. A refined history based rapidly-exploring random tree (RRT) algorithm which bias the growth of the tree based on its planning history is proposed and employed in the planning phase where the path is simple but the space is highly constrained. A novel adaptive RRT algorithm is developed for the path planning problem with challenging scenarios and uncertain environment. With extending values assigned on each tree node and extending schemes applied, the tree can adapts its growth to explore complex environments more efficiently. Experiments on the key algorithms are carried out and comparisons are made between the conventional path planning algorithms and the presented ones. The comparing results show that based on the proposed algorithms, the path planner can compute assembly path in challenging complex environments more efficiently and with higher success. This research provides the references to the study of computational assembly path planning under complex environments.     

机器人钣金折弯路径规划与仿真研究

针对钣金折弯机器人示教编程过程烦琐、效率低的问题,提出一种基于 Coin3D 的折弯机器人运动仿真系统方案。基于 Coin3D 虚拟场景技术,为折弯单元各组件建模,完成折弯单元加工环境的参数化配置和导入,实现仿真环境构建。为适应钣金工件随折弯加工逐步变形的特点,设计了对应的双向链式数据模型;分析了折弯机器人典型操作任务目标位姿的确定方法,并在此基础上参考人工示教经验,提出折弯机器人路径规划方法,实现了折弯机器人折弯加工的运动仿真。仿真实验验证了仿真系统和相关模型与方法的正确性,为折弯机器人离线编程系统研发奠定了基础。     

Generation and Simulation of Robot Trajectories in a Virtual CAD-Based Off-Line Programming Environment

This paper presents a new approach to the generation and optimisation of the position and orientation trajectories in Cartesian task space, and simulation in a virtual CAD-based off-line programming environment. A novel concept of the robot pose ruled surface is proposed, and defined as a motion locus of the robot orientation vector, i.e. the vector of equivalent angular displacement. The planning for trajectories of robot end-effectors can be accomplished by generating the robot pose ruled surface and optimising its area under the constraints with good kinematics and dynamics performances. The established optimisation model is based on functional analysis and dynamics planning, and is simplified by using high-order polynomial space curves as the robotic position and orientation trajectories. The developed system, RoboSim, is a virtual integrated environment which can be used as a testbed for automatic motion planning and simulation for robots. Two examples are given to verify the feasibility of the proposed approach and models, and to demonstrate the capabilities of generation, optimisation, and simulation modules and libraries in the RoboSim package. The simulation results show that the approach and system are feasible and useful for motion planning, performance analysis and evaluation, and CAD-based prototyping and off-line programming in both the virtual and the real design and planning environment.     

Local collision avoidance of multiple robots using avoidability measure and relative distance

This paper presents a new method driving multiple robots to their goal position without collision. To consider the movement of the robots in a work area, we adopt the concept of avoidability measure. The avoidability measure figures the degree of how easily a robot can avoid other robots considering the velocity of the robots. To implement the concept to avoid collision among multiple robots, relative distance between the robots is proposed. The relative distance is a virtual distance between robots indicating the threat of collision between the robots. Based on the relative distance, the method calculates repulsive force against a robot from the other robots. Also, attractive force toward the goal position is calculated in terms of the relative distance. These repulsive force and attractive force are added to form the driving force for robot motion. The proposed method is simulated for several cases. The results show that the proposed method steers robots to open space anticipating the approach of other robots. In contrast, since the usual potential field method initiates avoidance motion later than the proposed method, it sometimes fails preventing collision or causes hasty motion to avoid other robots. The proposed method works as a local collision-free motion coordination method in conjunction with higher level of task planning and path planning method for multiple robots to do a collaborative job.