Dual-layer multi-robot path planning in narrow-lane environments under specific traffic policies

Collision-free path planning is indispensable for the multi-robot system. Many existing multi-robot path planning algorithms may no longer work properly in the narrow-lane environment. We propose in this paper a dual-layer algorithm to deal with the multi-robot path planning problem in the narrow-lane environment. In the first layer, the integer programming technique primarily based on distance metrics balances the optimality of the generated collision-free paths and the computation time of the algorithm. In the second layer, fast feasible heuristics are applied to make sure the solvability of the proposed integer programming approach in the first layer. In the dual-layer algorithm, specific traffic policies for each narrow lane are implemented to generate a collision-free path for every robot while maintaining the narrow lane free, besides the collision avoidance approach at the robotic level. With this, inter-robot collision in the narrow lane is avoided, and the algorithm’s efficiency in producing collision-free paths increases. Simulations have been launched considerably based on the proposed assessment metrics. According to the extensive simulation data, our algorithm suggests a higher overall performance in the narrow-lane environment when in contrast with the present optimal, sub-optimal, and polynomial-complexity algorithms.

     

A kinematics and dynamics simulation of the IBM-7565 robot using AML

This article presents a kinematics and dynamics simulation of the IBM-7565 robot using its AML programming language. The kinematics and dynamics models are formulated according to the Denavit-Hartenberg convention and a recursive Newton-Euler algorithm, respectively. The simulation is integrated in a CAD software package (CATIA) which is used in robot offline programming and collision/interference analysis. The CAD package software which runs on an IBM 3033 main frame also emulates the AML for automatic programming. The simulation models can be run on the IBM 3033 using the emulator or on the robot's dedicated Series-1 computer to where the programs are downloaded for execution and control of robot motion.     

实现机器人动态路径规划的仿真系统

针对机器人动态路径规划问题,提出了在动态环境中移动机器人的一种路径规划方法,适用于环境中同时存在已知和未知,静止和运动障碍物的复杂情况。采用栅格法建立机器人空间模型,整个系统由全局路径规划和局部避碰规划两部分组成。在全局路径规划中,用快速搜索随机树算法规划出初步全局优化路径,局部避碰规划是在全局优化路径的同时,通过基于滚动窗口的环境探测和碰撞规则,对动态障碍物实施有效的局部避碰策略,从而使机器人安全顺利地到达目的地。仿真实验结果说明该方法具有可行性。     

一种基于机器人的航天器大型部件自主装配方法

航天器大型部件在狭小空间中装配存在着视野受限、目标位置不可见等问题,传统的吊装方法无法精确调整位姿、磕碰风险极高．本文提出一种基于双目视觉定位的机器人辅助装配路径规划方法．该方法以航天器、待安装部件以及机器人等装配要素的3维模型为基础,采用双目视觉系统对航天器上安装位置的几何特征进行精确定位．利用测量结果确定机器人和航天器之间的相对位姿关系,进而构建航天器装配现场的虚拟环境,识别装配过程中的几何约束,然后利用轴对齐包围盒方法进行碰撞检测,采用随机路图法规划出一条无干涉的装配路径,最后利用离线编程技术生成机器人可执行的装配序列．以某型号航天器激光测高仪为对象开展装配试验,完成了大型部件在狭小凹舱内的无磕碰安装．结果表明该方法可以实现对螺纹孔精准定位,快速规划出无干涉装配路径,能够控制机器人安全、高效完成大型部件在狭小空间下的安装作业．     

基于时间窗的AGV动态避碰路径规划方法

为了解决多AGV在动态不稳环境下的无碰撞路径规划和系统效率提升的问题,提出了基于时间窗的AGV无碰撞路径规划方法。首先建立了多AGV的避碰模型,并结合时间窗模型,将多AGV的无碰撞路径规划分为预先规划和实时规划两阶段,预先规划阶段进行多AGV无冲突时间窗的计算和最大化系统中AGV的流通量,实时规划阶段通过改变AGV在避碰模型上的占用优先级和局部重规划的方法进行动态避碰。最后以某智能仓储为应用案例进行仿真实验,证明了该算法能有效避免多AGV的碰撞,提高AGV的流通量,同时在动态环境下具有较好的鲁棒性和柔性。     

A blackboard system for the off-line programming of Robots

This paper describes the use of the blackboard architecture for the off-line programming of an IMB 7565 Robot. A blackboard system was implemented in PROLOG and it has been applied successfully for the automatic generation of a control code for the robot to perform the task of block assembly in an environment with an obstacle. The opportunistic type of problem-solving offered by the blackboard architecture has succeeded in obtaining a solution. The user-interface to the system is represented as a knowledge source in the blackboard system, which allows the user to modify the goal specifications during the operation of the blackboard system.     

Planning of collision-free paths for a reconfigurable dual manipulator equipped mobile robot

In this paper, we study the problem of finding a collision-free path for a mobile robot which possesses manipulators. The task of the robot is to carry a polygonal object from a starting point to a destination point in a possibly culttered environment. In most of the existing research on robot path planning, a mobile robot is approximated by a fixed shape, i.e., a circle or a polygon. In our task planner, the robot is allowed to change configurations for avoiding collision. This path planner operates using two algorithms: the collision-free feasible configuration finding algorithm and the collision-free path finding algorithm. The collision-free feasible configuration finding algorithm finds all collision-free feasible configurations for the robot when the position of the carried object is given. The collision-free path finding algorithm generates some candidate paths first and then uses a graph search method to find a collision-free path from all the collision-free feasible configurations along the candidate paths. The proposed algorithms can deal with a cluttered environment and is guaranteed to find a solution if one exists.     

A path planning algorithm for industrial robots

Instead of using the tedious process of robot teaching, an off-line path planning algorithm has been developed for industrial robots to improve their accuracy and efficiency. Collision avoidance is the primary concept to achieve such goal. By use of the distance maps, the inspection of obstacle collision is completed and transformed to the configuration space in terms of the robot joint angles. On this configuration map, the relation between the obstacles and the robot arms is obvious. By checking the interference conditions, the collision points are indicated with marks and collected into the database. The path planning is obtained based on the assigned marked number of the passable region via wave expansion method. Depth-first search method is another approach to obtain minimum sequences to pass through. The proposed algorithm is experimented on a 6-DOF industrial robot. From the simulation results, not only the algorithm can achieve the goal of collision avoidance, but also save the manipulation steps.     

Collision-free motion of an articulated kinematic chain in adynamic environment

A method for the collision avoidance of an articulated kinematic chain in a dynamic environment is presented. The inverse kinematic solution is used to get the configuration of the chain for a given position of any part of the chain. The calculation of collision-free motion is based on the local information about the motion. Intermediate positions are used to get the new motion path of the chain. The movement of environmental objects during the collision detection and the generation of new motions are considered. This generalizes the method for arbitrarily configured kinematic chains and for a dynamic environment. Its implementation for the motion planning of robot manipulators in an offline programming system is briefly described     

Path planning for robobt manipulators in polyhhedral objects environment

A recent development in robotics is the increase of intelligence in robots. One of the research fields is to enable robots to autonomously avoid collisions with surrounding objects. This article presents an efficient method for planning collision-free paths for an articulated robot that is surrounded by polyhedral objects. The algorithm plans a hypothetical Archimedes's spiral path from the initial position to the goal position. When a collision among the arms and obstacles is detected, the hypothetical path will be modified to avoid the collision. The algorithm applies geometric methods to determine the upper and lower bounds of the reachable area of the wrist and then determines a collision-free path point on that reachable area. Because the equations, which represent the upper and lower bounds, are simple, the algorithm can rapidly determine a collision-free path. Moreover, with minor modifications, this path planning algorithm can also be applied to other robots such as spherical, cylindrical, and Cartesian types of robots. © 1995 John Wiley & Sons, Inc.     

融合动态障碍物运动信息的路径规划算法

传统的路径规划算法只能在障碍物不发生位置变化的环境中计算最优路径。但是随着机器人在商场、医院、银行等动态环境下的普及,传统的路径规划算法容易与动态障碍物发生碰撞等危险。因此,关于随机动态障碍物条件下的机器人路径规划算法需要得到进一步改善。为了解决在动态环境下的机器人路径规划问题,提出了一种融合机器人与障碍物运动信息的改进动态窗口法来解决机器人在动态环境下的局部路径规划问题,并且与优化A*算法相结合来实现全局最优路径规划。主要内容体现为：在全局路径规划上,采用优化A*算法求解最优路径。在局部路径规划上,以动态障碍物的速度作为先验信息,通过对传统动态窗口法的评价函数进行扩展,实现机器人在动态环境下的自主智能避障。实验证明,该算法可以实现基于全局最优路径的实时动态避障,具体表现为可以在不干涉动态障碍物的条件下减少碰撞风险、做出智能避障且路径更加平滑、长度更短、行驶速度更快。     

一种移动机器人在三维动态环境下的路径规划方法

提出一种基于遗传算法的三维动态环境下的路径规划方法,通过对机器人的运动行为进行编码,将各种约束条件融入到遗传算法当中,规划出可实际应用的避障路径,仿真研究表明该方法是简单有效的.     

基于双层模糊逻辑的多机器人路径规划与避碰

针对无通信情况下的多机器人系统在未知动态环境下的路径规划问题,设计了基于双层模糊逻辑的多机器人路径规划与动态避碰系统。方向模糊控制器充分考虑了障碍物的距离信息和目标的角度信息,转化为机器人与障碍物的碰撞可能性,从而输出转向角度实现机器人的动态避障;速度模糊控制器将障碍物的距离信息作为输入,将速度因子作为输出,提高了多机器人路径规划与动态避碰系统的效率和鲁棒性。在Pioneer3-DX机器人实体上验证了该系统的可行性。     

六轴工业机器人先验引导RRT*避障轨迹算法研究

针对六轴工业机器人装配避障路径运动问题,研究了机器人整体避障运动路径规划方法,提出一种RRT*改进算法;算法以RRT*算法为基础,在障碍物建模中引入包围盒算法,加入对机器人各轴与障碍物的碰撞检测;在路径规划中加入对随机点生成方向与树枝生长方向的先验引导机制,优化了算法路径长度与路径搜寻效率;通过Matlab进行了试验验证,结果表明与标准RRT*算法相比,先验引导RRT*算法缩短路径长度14%左右,且满足机器人末端路径与手臂各轴的避障需求。     

Parallel and diagonal parking in nonholonomic autonomous vehicles

This paper considers the problem of parallel and diagonal parking in wheeled vehicles. A method to plan in real-time a set of collision-free manoeuvres is presented. Artificial intelligent techniques, namely fuzzy logic, play an important role in the practical application of the method. Thus, a fuzzy system is used to select the most suitable manoeuvre from the solution set according with the environment, dealing with optimality, path tracking performance and collision avoidance trade-off. This technique has been implemented in a fuzzy behaviour-based control architecture combining planning and reactivity. The efficiency of the proposed method is demonstrated using the nonholonomic mobile robot ROMEO-3R designed and built at the University of Seville.     

Automatic motion planning for complex welding problems by considering angular redundancy

Automatic motion planning in complex environment is significant in manufacturing. This paper presents an off-line collision-free motion planning algorithm by considering the task redundancy existing in manufacturing. The paper takes a typical welding technique as an example, which mainly aims at solving the complex continuous welding motion planning problems. In the proposed algorithm, the angular redundancy existing in the welding process is fully considered for planning and optimizing the welding torch path by minimizing the torch angular cost. Besides, some strategies have been introduced to improve the efficiency of the proposed algorithm, such as the heuristic region sampling strategy based on Gaussian sampling, which is adopted to guide planning. Midpoint collision checking strategy is employed to improve the efficiency of the collision checking. The proposed algorithm is very effective in solving the complex welding motion planning problems, such as in the welding environment where the weld seam is situated in the narrow passage or the dense obstacles. The experiments are carried out to verify that our proposed algorithm is feasible in the relevant scenarios. All the experimental results show that not only the proposed algorithm could find a feasible collision-free path in the different complex environments if any path exists, but also the torch angle could be optimized with the increase of iteration.     

Study on the Configuration Space Based Algorithmic Path Planning of Industrial Robots in an Unstructured Congested Three-Dimensional Space: An Approach Using Visibility Map

Obstacle avoidance and subsequently collision-free path planning is a potential field of robotics research, specially in the perspective of today's industrial scenario. In this paper, the celebrated method, namely, Visibility Map is being used to generate feasible collision-free near-optimal safe path(s) for a three- dimensional congested robot workspace using heuristic algorithms. The final path is obtainable in terms of joint configurations, by considering the Configuration Space of the task-space. The developed algorithms have been verified by considering typical 2D workspaces at the onset, cluttered with different obstacles (convex and/or concave) with regular geometries and later on, with the real spatial manifold. The outcome of these algorithms has been found instrumental in programming an industrial robot in order to perform a series of task in the shop-floor. A case-study reveals the effectiveness of the heuristics involved in the developed algorithms, by virtue of the successful application in an unstructured industrial environment to carry out robotized material handling operation in real-time.     

Collision-free motion planning of dual-arm reconfigurable robots

Dual-arm reconfigurable robot is a new type of robot. It can adapt to different tasks by changing its different end-effector modules which have standard connectors. Especially, in fast and flexible assembly, it is very important to research the collision-free planning of dual-arm reconfigurable robots. It is to find a continuous, collision-free path in an environment containing obstacles. A new approach to the real-time collision-free motion planning of dual-arm reconfigurable robots is used in the paper. This method is based on configuration space (C-Space). The method of configuration space and the concepts reachable manifold and contact manifold are successfully applied to the collision-free motion planning of dual-arm robot. The complexity of dual-arm robots’ collision-free planning will reduce to a search in a dispersed C-Space. With this algorithm, a real-time optimum path is found. And when the start point and the end point of the dual-arm robot are specified, the algorithm will successfully get the collision-free path real time. A verification of this algorithm is made in the dual-arm horizontal articulated robot SCARATES, and the simulation and experiment ascertain that the algorithm is feasible and effective.     

Real-time Velocity Alteration Strategy for Collision-free Trajectory Planning of Two Articulated Robot Manipulators

Two articulated robots working in a shared workspace can be programmed by planning the tip trajectory of each robot independently. To account for collision avoidance between links, a real-time velocity alteration strategy based on fast and accurate collision detection is proposed in this paper to determine the step of next motion of slave (low priority) robot for collision-free trajectory planning of two robots with priorities. The effectiveness of the method depends largely on a newly developed method of accurate estimate of distance between links. By using the enclosing and enclosed ellipsoids representations of polyhedral models of links of robots, the minimum distance estimate and collision detection between the links can be performed more efficiently and accurately. The proposed strategy is implemented in an environment where the geometric paths of robots are pre-planned and the preprogrammed velocities are piecewise constant but adjustable. Under the control of the proposed strategy, the master robot always moves at a constant speed. The slave robot moves at the selected velocity, selected by a tradeoff between collision trend index and velocity reduction in one collision checking time, to keep moving as far as possible and as fast as possible while avoid possible collisions along the path. The collision trend index is a fusion of distance and relative velocity between links of two robots to reflect the possibility of collision at present and in the future. Graphic simulations of two PUMA560 robot arms working in common workspace but with independent goals are conducted. Simulations demonstrate the collision avoidance capability of the proposed approach as compared to the approach based on bounding volumes. It shows that advantage of our approach is less number of speed alterations required to react to potential collisions.     

Path planning strategy for autonomous mobile robot navigation using Petri-GA optimisation

In this paper, a novel knowledge based genetic algorithm (GA) for path planning of multiple robots for multiple targets seeking behaviour in presence of obstacles is proposed. GA technique has been incorporated in Petri-Net model to make an integrated navigational controller. The proposed algorithm is based upon an iterative non-linear search, which utilises matches between observed geometry of the environment and a priori map of position locations, to estimate a suitable heading angle, there by correcting the position and orientation of the robots to find targets. This knowledge based GA is capable of finding an optimal or near optimal robot path in complex environments. The Petri-GA model can handle inter robot collision avoidance more effectively than the stand alone GA. The resulting navigation algorithm has been implemented on real mobile robots and tested in various environments to validate the developed control scheme.