基于改进深度强化学习的三维环境路径规划

提出一种改进深度强化学习算法(NDQN),解决传统Q-learning算法处理复杂地形中移动机器人路径规划时面临的维数灾难.提出一种将深度学习融于Q-learning框架中,以网络输出代替Q值表的深度强化学习方法.针对深度Q网络存在严重的过估计问题,利用更正函数对深度Q网络中的评价函数进行改进.将改进深度强化学习算法与...     

Dynamic method for software test data generation

Test data generation in program testing is the process of identifying a set of test data which satisfies a given testing criterion. Existing pathwise test data generators proceed by selecting program paths that satisfy the selected criterion and then generating program inputs for these paths. One of the problems with this approach is that unfeasible paths are often selected; as a result, significant computational effort can be wasted in analysing those paths. In this paper, an approach to test data generation, referred to as a dynamic approach for test data generation, is presented. In this approach, the path selection stage is eliminated. Test data are derived based on the actual execution of the program under test and function minimization methods. The approach starts by executing a program for an arbitrary program input. During program execution for each executed branch, a search procedure decides whether the execution should continue through the current branch or an alternative branch should be taken. If an undesirable execution flow is observed at the current branch, then a real-valued function is associated with this branch, and function minimization search algorithms are used to locate values of input variables automatically, which will change the flow of execution at this branch.     

概率模型检测技术在机器人路径规划中的应用

在机器人路径规划的实际应用中,针对机器人移动行为可能会受到外界环境影响的难题,提出了一种采用概率模型检测技术进行路径规划的新方法。首先,分析环境中的主要影响因素,将机器人的移动行为看作一个不确定事件,构建马尔可夫决策过程(MDP)模型。然后,采用概率计算树逻辑(PCTL)公式描述模型属性,表达机器人复杂多样的目标任务。最后,运用PRISM平台对模型进行分析和验证,得到满足属性的全局优化路径和定量数据。仿真结果表明,上述方法不仅能够保障机器人在障碍物环境中无碰撞移动,而且可以避开环境相对复杂的区域,保证机器人以最大概率完成任务。对比试验证明上述方法的正确性和有效性。     

一种改进的分层路网的路径规划算法应用

为了提高路径规划效率,提出一种改进的分层路网的路径规划算法。首先,城市路网进行分层处理,以经典A*算法为核心,在高层路网上使用改进机制,评估函数做相应调整,然后,对其权值设置上下限阈值,提高算法的搜索精度及搜索效率。实验结果表明,规划的路径并非Dijkstra算法的最短,但是改进的算法使快速路段所占比例达90%以上,实际运行最优。     

大数据支持下考虑障碍避让的机器人路径规划

为了使机器人在未知环境内可以成功规划出躲避障碍物的最短路径,在大数据支持下,设计了一种考虑障碍避让的机器人路径规划方法.首先分析机器人障碍物避让原理,确定机器人能够自由活动的范围.然后通过蚂蚁族群觅食流程对存在障碍物的路径进行模拟,获得基础路径规划结果,随后凭借赌轮盘规则细化,挑选节点通过机器人滚动窗口内映射,从而确定...     

Efficient collision-free path-planning of multiple mobile robots system using efficient artificial bee colony algorithm

This paper aims to propose a novel design approach for on-line path planning of the multiple mobile robots system with free collision. Based on the artificial bee colony (ABC) algorithm, we propose an efficient artificial bee colony (EABC) algorithm for solving the on-line path planning of multiple mobile robots by choosing the proper objective function for target, obstacles, and robots collision avoidance. The proposed EABC algorithm enhances the performance by using elite individuals for preserving good evolution, the solution sharing provides a proper direction for searching, the instant update strategy provides the newest information of solution. By the proposed approach, the next positions of each robot are designed. Thus, the mobiles robots can travel to the designed targets without collision. Finally, simulation results of illustration examples are introduced to show the effectiveness and performance of the proposed approach.     

Path Loss Modelling for Location Service Applications

The aim of this paper is the path loss modelling for the radiolocation services in radio communication networks, particularly in cellular networks. The main results of the measurements obtained in the physical layer of the UMTS are introduced. A new method for the utilization of the multipath propagation phenomenon to improve the estimation of the distance between the MS （mobile station） and the BS （base station） is outlined. This method significantly increases the quality of location services in systems which use a radio interface with DS （direct sequence） CDMA （code division multiple access）.     

基于机器视觉的快速切割路径生成系统

针对当前电路板切割路径生成方法效率低、自动化程度低等特点,设计一种基于机器视觉的快速切割路径生成系统。利用图像采集装置获取加工视场,通过图像编辑器对加工视场进行编辑,系统自动生成加工程序,加工参数可复用,加工路径可动态模拟。测试结果表明,该系统操作简单、快捷、自动化程度高。     

Sampling-Based Tabu Search Approach for Online Path Planning

Abstract

Path planning in unknown environments is one of the most challenging research areas in robotics. In this class of path planning, the robot acquires the information from its sensory system. Sampling-based path planning is one of the famous approaches with low memory and computational requirements that has been studied by many researchers during the past few decades. We propose a sampling-based algorithm for path planning in unknown environments using Tabu search. The Tabu search component of our method guides the sampling to find the samples in the most promising areas and makes the sampling procedure more intelligent. The simulation results show the efficient performance of the proposed approach in different types of environments. We also compare the performance of the algorithm with some of the well-known path planning approaches, including Bug1, Bug2, SRT, potential fields and the visibility graph. Furthermore, two different sampling strategies were used in the sampling procedure, including uniform and Gaussian distributions.     

A survey on coverage path planning for robotics

Coverage Path Planning (CPP) is the task of determining a path that passes over all points of an area or volume of interest while avoiding obstacles. This task is integral to many robotic applications, such as vacuum cleaning robots, painter robots, autonomous underwater vehicles creating image mosaics, demining robots, lawn mowers, automated harvesters, window cleaners and inspection of complex structures, just to name a few. A considerable body of research has addressed the CPP problem. However, no updated surveys on CPP reflecting recent advances in the field have been presented in the past ten years. In this paper, we present a review of the most successful CPP methods, focusing on the achievements made in the past decade. Furthermore, we discuss reported field applications of the described CPP methods. This work aims to become a starting point for researchers who are initiating their endeavors in CPP. Likewise, this work aims to present a comprehensive review of the recent breakthroughs in the field, providing links to the most interesting and successful works.