Collision avoidance for Robot manipulators: Application to Catia/IBM 7565 interface

A collision avoidance algorithm has been developed to augment the capability of an automatic (off-line) robot path planning (programming) tool. The use of off-line programming tools for robot task programming is becoming increasingly important, but the advantages to be gained by off-line programming may be lost if collision-free path planning capabilities are not included. This article addressed the problem of collision-free path planning in the context of a gantry type robot. The collision avoidance algorithm described here uses the <heuristic approach> to collision-free path planning. The manipulator and obstacles are modeled as spheres to simplify tests for collision. An important feature of this algorithm is that it permits the manipulation of objects in the robot's environment. When compared against an algorithm from the literature, given a lightly cluttered environment modelled by spheres, the new algorithm finds a collision-free path much faster. This new algorithm has been implemented as part of the CATIA/IBM 7565 interface which forms an automatic off-line programming system for the IBM 7565 robot. It has also been implemented as a supervisory collision filter to allow collision-free control of the robot from the operator's console. In both cases the algorithm has been demonstrated to provide efficient and effective collision avoidance for the IBM 7565 robot.     

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.     

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.     

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 bayesian approach to real-time obstacle avoidance for a mobile robot

Real-time obstacle avoidance is essential for the safe operation of mobile robots in a dynamically changing environment. This paper investigates how an industrial mobile robot can respond to unexpected static obstacles while following a path planned by a global path planner. The obstacle avoidance problem is formulated using decision theory to determine an optimal response based on inaccurate sensor data. The optimal decision rule minimises the Bayes risk by trading between a sidestep maneuver and backtracking to follow an alternative path. Real-time implementation is emphasised here as part of a framework for real world applications. It has been successfully implemented both in simulation and in reality using a mobile robot.     

DETERMINING THE PATH SEARCH GRAPH AND FINDING A COLLISION-FREE PATH BY THE MODIFIED A* ALGORITHM FOR A 5-LINK CLOSED CHAIN

Two tightly coordinated 2-link planar manipulators and the straight line between their two bases can be considered as a 5-link closed chain. Since the coordination of robot manipulators has broad applications in manufacturing, hazardous material handling, undersea operation, and space exploration, automatic collision-free path planning for a 5-link closed chain is an important unsolved engineering problem. This paper describes a collision-free path planning algorithm for a 5-link closed chain with revolute joints. In the algorithm the 5-link closed chain is first represented by a path search graph that is built on the basis of the concept of the newly developed C subspace model. Subsequently, a collision-free path is searched upon the graph by the modified A* algorithm. The significance of this path planning algorithm is its convergence and efficiency. The convergence is guaranteed by the C subspace model, which constructs unique mapping between the planned path in C subspaces and that in the world space. The way we build the path search graph and evaluation functions of the A* algorithm is designed to increase the search speed and to preserve the maneuverability of the 5-link closed chain.     

Task Planning For A Mobile Robot In An Indoor Environment Using Object-oriented Domain Information

For a mobile robot to be practical, it needs to navigate in dynamically changing environments and manipulate objects in the environment with operating ease. The main challenges to satisfying these requirements in mobile robot research include the collection of robot environment information, storage and organization of this information, and fast task planning based on available information. Conventional approaches to these problems are far from satisfactory due to their requirement of high computation time. In this paper, we specifically address the problems of storage and organization of the environment information and fast task planning in the area of robotic research. We propose an special object-oriented data model (OODM) for information storage and management in order to solve the first problem. This model explicitly represents domain knowledge and abstracts a global perspective about the robot's dynamically changing environment. To solve the second problem, we introduce a fast task planning algorithm that fully uses domain knowledge related to robot applications and to the given environment. Our OODM based task planning method presents a general frame work and representation, into which domain specific information, domain decomposition methods and specific path planners can be tailored for different task planning problems. This method unifies and integrates the salient features from various areas such as database, artificial intelligence, and robot path planning, thus increasing the planning speed significantly     

Joint trajectory generation for redundant robots in an environment with obstacles

Collision avoidance is an absolutely essential requirement for a robot to complete a task in an environment with obstacles. For kinematically redundant robots, collision avoidance can be achieved by making full use of the redundancy. In this article, the problem of determining collision-free joint space trajectories for redundant robots in an environment with multiple obstacles is considered, and the “command generator” approach is employed to generate such trajectories. In this approach, a nondifferentiable distance objective function is defined and is guaranteed to increase wherever possible along the trajectory through a vector in N(J), the null space of Jacobian matrix J. Algorithms that implement this nondifferentiable optimization problem are fully developed. It is shown that the proposed collision-free trajectory generation scheme is efficient and practical. Extensive simulation results of a four-link robot example are presented and analyzed.     

移动机器人的动态路径规划及控制

本文阐述了两类机器人的导航方法:第一类方法是,先生成整个路径,然后进行路径跟踪控制;第二类方法是所谓的势场方法,即利用人工势场直接进行运动控制.在此基础上,我们提出了用于移动机器人系统导航的动态路径规划-控制方法.系统根据环境信息对路径进行动态的生成与控制,从而与实际环境实现了闭环,增加了对系统的稳定性和对环境的适应能力.     

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。     

Planning 3-D Collision-Free Dynamic Robotic Motion Through Iterative Reshaping

We propose a general and practical planning framework for generating 3-D collision-free motions that take complex robot dynamics into account. The framework consists of two stages that are applied iteratively. In the first stage, a collision-free path is obtained through efficient geometric and kinematic sampling-based motion planning. In the second stage, the path is transformed into dynamically executable robot trajectories by dedicated dynamic motion generators. In the proposed iterative method, those dynamic trajectories are sent back again to the first stage to check for collisions. Depending on the application, temporal or spatial reshaping methods are used to treat detected collisions. Temporal reshaping adjusts the velocity, whereas spatial reshaping deforms the path itself. We demonstrate the effectiveness of the proposed method through examples of a space manipulator with highly nonlinear dynamics and a humanoid robot executing dynamic manipulation and locomotion at the same time.      

Dynamic path planning for a planar articulated robot arm moving amidst unknown obstacles

This work is concerned with planning collision-free paths for a robot arm moving in an environment filled with unknown obstacles, where any point of the robot body is subject to collision. To compensate for the uncertainty, the system is provided with sensory feedback information about its immediate surroundings. In such a setting, which presents significant practical and theoretical interest, human intuition is of little help, and designing algorithms with proven convergence thus becomes an important task. We show that, given the target position, local feedback information is sufficient to guarantee reaching a global objective (the target position) and present a nonheuristic algorithm which generates reasonable—if, in general, not optimal—collision-free paths. In this approach, the path is being planned continuously (dynamically), based on the arm's current position and on the sensory feedback. Here, a case of a planar arm with two revolute joints is studied. No constraints on the shape of the robot links or the obstacles are imposed. The general idea is to reduce the problem of motion planning to an analysis of simple closed curves on the surface of an appropriate two-dimensional manifold.     

An efficient local approach for the path generation of robot manipulators

In this article an efficient local approach for the path generation of robot manipulators is presented. The approach is based on formulating a simple nonlinear programming problem. This problem is considered as a minimization of energy with given robot kinematics and subject to the robot requirements and a singularities avoidance constraint. From this formulation a closed form solution is derived which has the properties that allows to pursue both singularities and obstacle avoidance simultaneously; and that it can incorporate global information. These properties enable the accomplishment of the important task that while a specified trajectory in the operational space can be closely followed, also a desired joint configuration can be attained accurately at a given time. Although the proposed approach is primarily developed for redundant manipulators, its application to nonredundant manipulators is examplified by considering a particular commercial manipulator.     

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.     

面向地图构建的移动机器人局部路径自主规划

移动机器人在未知场景中规划路径以自主完成定位与地图构建是机器人领域的一个重要研究课题.本文阐述了一种利用实时构建的信息熵地图动态生成机器人的局部探索路径,并综合转向约束和避障约束设计了一种基于模糊评价方法的方向选择策略跟踪生成的局部路径并进行环境构图.与现有方法相比,本文方法能够根据环境动态地生成平滑连续的局部探索路径,并能引导机器人进行障碍物躲避和完成自主构图.实验结果表明相较对比方法,本文方法的探索路程最短,观测覆盖度最高,同时整个自主构图过程所需的时间也更短.     

Minimum distance collision-free path planning for industrial robots with a prismatic joint

A collision-free path is a path which an industrial robot can physically take while traveling from one location to another in an environment containing obstacles. Usually the obstacles are expanded to compensate for the body width of the robot. For robots with a prismatic joint, which allows only a translational motion along its axis, additional problems created by the long boom are handled by means of pseudoobstacles which are generated by real obstacle's edges and faces. The environment is then modified by the inclusion of pseudoobstacles which contribute to the forbidden regions. This process allows the robot itself again to be represented by a point specifying the location of its end effector in space. An algorithm for determining the shortest distance collision-free path given a sequence of edges to be traversed has been developed for the case of stationary obstacles.     

A real-time limit-cycle navigation method for fast mobile robots and its application to robot soccer

A mobile robot should be designed to navigate with collision avoidance capability in the real world, flexibly coping with the changing environment. In this paper, a novel limit-cycle navigation method is proposed for a fast mobile robot using the limit-cycle characteristics of a 2nd-order nonlinear function. It can be applied to the robot operating in a dynamically changing environment, such as in a robot soccer system. By adjusting the radius of the motion circle and the direction of obstacle avoidance, the navigation method proposed enables a robot to maneuver smoothly towards any desired destination. Simulations and real experiments using a robot soccer system demonstrate the merits and practical applicability of the proposed method.     

基于改进模糊算法的移动机器人避障

为了提高移动机器人在连续障碍物环境下的避障性能,提出了一种具有速度反馈的模糊避障算法。移动机器人利用超声传感器感知周围环境,在模糊控制的基础上通过障碍物分布情况调整自身速度,进而引入优雅降级并把改进的模糊避障融入其中,增强了移动机器人的鲁棒性。实验结果表明,该方法能通过与环境交互调整机器人移动速度,控制机器人成功避障并优化避障路径,具有良好的有效性。     

Collision-avoidance trajectory planning using tube concept: Analysis and simulation

The concept of a tube is introduced and is applied to the solving of the collision-avoidance, minimum-time trajectory planning problem. A collision-free space is represented by an articulated tube with parameters of reference points and path tolerances. For obstacle avoidance, the end effector is constrained to move inside of the tube. An algorithm which will find suboptimal solutions for optimizing both path and velocity history of the trajectory by the use of piecewise joint-space polynomials is presented. This algorithm exploits the robot arm dynamics in realistic environments where obstacles are present and the minimization of task time is desired with smooth motion. Experimental results show that as the path tolerance increases the new algorithm takes advantage of the spatial freedom to provide solutions superior to conventional approaches and to methods based on predefined paths.     

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.