基于力流和有限元法的路径规划

提出了一种基于力流和有限元法的路径规划方法,旨在解决复杂环境下全局路径规划的问题。将地图等效为由杆单元构成的桁架结构,在起点和终点处施加静定约束条件和相互作用力,通过捕捉点到点的力流解决避障和路径规划问题。力在物体中的传递遵循最短路径原则,因此力流路径不会偏离最优路径太远。根据上述原理设计了基于杆单元的路径规划算法,以简单桁架模型对路径计算过程进行详细演示,并分析了网格对计算效率的影响,证明了算法的可行性。在复杂迷宫地图中用本文算法与A*算法进行对比,结果显示本方法在大规模和复杂地图上具有优势,有限元法的网格构建方式比A*算法更自由,因此使计算规模更加容易控制。

基于适应度函数的无人船遗传算法航径规划

遗传算法通过适应度函数选取最优的路径,采用了无人船转弯半径来改进适应度函数,实现无人船遗传算法航径规划;考虑到无人船机动性能对航迹平滑性的要求,在初始种群中利用贝塞尔曲线优化方法,将原有的折线路径优化成光滑的曲线路径;在适应度函数中添加曲率判断,以无人船最小转弯半径为约束条件,设置曲线路径的最大曲率,最后通过适应度函数筛选出符合约束条件的光滑路径;仿真结果表明,所提出的方法能获得符合无人船最小转弯半径约束的光滑路径,相比于平滑算法,该方法的曲率更小,收敛速度更快。

四旋翼无人机航径规划遗传算法研究

提出了一种改进遗传算法,用于对复杂环境中的四旋翼无人机进行航径规划。针对最优航径长度进行了方法改进,将航径长度、平滑度、安全性三者相结合,形成了一个目标航径规划问题。采用改进遗传算法来改善连续空间中的初始航径,并找到起始位置和目标位置之间的最佳航径。为了评估验证所提出改进算法的有效性,进行了大量的仿真实验。研究表明,改进后的遗传算法在航径长度、运行时间、成功率方面可以达到更好的效果,最后通过仿真,证明了该改进算法对四旋翼无人机航径规划问题的有效性。所提出的改进算法能够确定最优航径。

基于IRP的城市配电网优化规划设计问题探讨

通过运用综合资源规划的基本原理,在分析某居民小区用电负荷特性的基础上,设计一个基准负荷和一个用于小区配电DSM规划的负荷半径,建立电网公司在对负荷小区实行DSM规划时的数学模型,并且在不同的激励系数时.得到相应的电网公司设施DSM时积极性百分比参数,从而认为只有在平衡激励及以上的情况下才能保证DSM的顺利进行。同时认为只有选择适当的基准负荷和规划半径才能更好地发挥DSM的作用。

月球车的视觉和自主导航系统

基于当前对于月球车、火星登陆机器人等的研究结果 ,介绍了月球车的视觉系统、控制方案和路径规划方法 。

Research on global path planning based on ant colony optimization for AUV

Path planning is an important issue for autonomous underwater vehicles （AUVs） traversing an unknown environment such as a sea floor, a jungle, or the outer celestial planets. For this paper, global path planning using large-scale chart data was studied, and the principles of ant colony optimization （ACO） were applied. This paper introduced the idea of a visibility graph based on the grid workspace model. It also brought a series of pheromone updating rules for the ACO planning algorithm. The operational steps of the ACO algorithm are proposed as a model for a global path planning method for AUV. To mimic the process of smoothing a planned path, a cutting operator and an insertion-point operator were designed. Simulation results demonstrated that the ACO algorithm is suitable for global path planning. The system has many advantages, including that the operating path of the AUV can be quickly optimized, and it is shorter, safer, and smoother. The prototype system successfully demonstrated the feasibility of the concept, proving it can be applied to surveys of unstructured unmanned environments.

Design and Realization of Simple Intelligent Robotic Lawn Mower Based on Arduino Mega2560

Robotic lawn mowers available in markets are much more complicated with high cost, hence, a new robot is designed in the research. In detail, the control system is made up of Arduino Mega2560 and 11 sensors and the robot works with four wheels （two front and back wheels） driven by an electric motor. Furthermore, the platform of lawn-mowing is designed semicircle, equipped with three small high- speed and low-power electric motors; the cutting distance is determined by width of motherboard. In addition, the hardware of the system is made up of circuit control and working machines, of which the former includes a single chip unit, a wireless remote control, a sensor unit, an infrared array module, a driving module of electric motor, a display unit and a power source; the latter includes a mowing platform and a sensor window. In addition, the related software is programmed using C language and modular programming involving PWM program, Hall sensor program, liquid-crys- tal display, tilt program, supersonic sounding program, infrared obstacle-avoidance program, parking program, and remote control program. After hardware was adjust- ed, the robotic lawn mower was tested for multiple times in a standard lawn, and a satisfied effect was achieved.

Path Planning Algorithm for Car-like Robot and Its Application

The problem of path planning is studied for t he case for a mobile robot moving in a known environment. An aggressive algorith m using a description of the obstacles based on a neural network is proposed. Th e algorithm allows to construct an optimal path which is piecewise linear with c hanging directions of the obstacles and the calculation speed for the proposed a lgorithm is comparatively fast. Simulation results and an application to a car_l ike robot 'Khepera' show the effectiveness of the proposed algorithm.

高速铁路网络能力计算研究

充分考虑高速铁路网络作为多级递阶控制系统的复杂性和对旅客运输服务质量的要求,构建基于时段特定场景的高速铁路列车服务与需求意向集合(t@n-tsdis,train service-demand intention set at network),定义以完成这个集合所需基础设施占用时间为网络能力的衡量标准。提出了两阶段的优化计算方法,并提出多目标优化改进的Pareto(1+1)—PAES算法流程,采用交互式滚动优化策略处理整数约束条件、模糊逻辑罚函数法处理连续实数约束条件、Pareto存档进化策略求解多目标优化问题。以某高速铁路网络为例进行能力计算,验证了模型与算法的有效性。

Radial Based Probabilistic Roadmap Motion Planning Method in Sparse Environment

A new dynamic path planning method in high dimensional workspace, radial based probabilistic roadmap motion (RBPRM) planning method, is presented. Different from general probabilistic roadmap motion planning methods, it uses straight lines as long as possible to construct a path graph, so the final path obtained from the graph is relatively shorter and straighter. Experimental results show the efficiency of the algorithm in finding shorter paths in sparse environment.

Tactical planning and optimization of a milk run system of parts pickup for an engine manufacturer

A real-life milk run system designing problem of an engine manufacturer adopted JIT(just-in-time)production is studied.In the process of milk run system planning and design,the supply base is identified and a supplier site map is plotted for an arrangement of routes on which parts are periodically collected in a JIT manner from many scattered suppliers.With unit load designing,vehicle choosing and fleet sizing,pickup routing,vehicle assigning and scheduling problems are studied.Among these problems,a CVRP problem is identified and formulated as the key optimization in designing this milk run system,and it is solved through an optimization process.This tactical planning and optimization process gives a good solution to the real problem,and may shed light on the planning of similar systems.

Robot coverage algorithm under rectangular decomposition environment

The environment modeling algorithm named rectangular decomposition, which is composed of cellular nodes and interleaving networks, is proposed. The principle of environment modeling is to divide the environment into individual square sub-areas. Each sub-area is orientated by the central point of the sub-areas called a node. The rectangular map based on the square map can enlarge the square area side size to increase the coverage efficiency in the case of there being an adjacent obstacle. Based on this algorithm, a new coverage algorithm, which includes global path planning and local path planning, is introduced. In the global path planning, uncovered subspaces are found by using a special rule. A one-dimensional array P, which is used to obtain the searching priority of node in every direction, is defined as the search rule. The array P includes the condition of coverage towards the adjacent cells, the condition of connectivity and the priorities defined by the user in all eight directions. In the local path planning, every sub-area is covered by using template models according to the shape of the environment. The simulation experiments show that the coverage algorithm is simple, efficient and adapted for complex two- dimensional environments.

An Evolutionary Programming Based on Hidden Neuron Modifiable Radial Basis Function Networks

In this paper, an improved radial basis function networks named hidden neuron modifiable radial basis function (HNMRBF) networks is proposed for target classification, and evolutionary programming (EP) is used as a learning algorithm to determine and modify the hidden neuron of HNMRBF nets. The result of passive sonar target classification shows that HNMRBF nets can effectively solve the problem of traditional neural networks, i. e. learning new target patterns on line will cause forgetting of the old patterns.

基于需求的高速铁路服务网络设计框架

高速铁路服务网络是在物理网的基础上依据客流需求特征而构建的供旅客出行选择的连通网络,是编制旅客列车开行方案和列车运行图的基础。我国高速铁路网规模大、构成复杂。本文分析了高速铁路旅客出行需求特征,提出了服务网络设计框架,依据分治策略将其分为四个阶段:高速铁路客运节点等级划分、列车运行路径规划、列车停站方案设计、换乘接续关系设计,并对每个环节进行了具体设计分析。

ROUTE OPTIMIZING ALGORITHM OF AIRPORT SURFACE BASED ON GIS

The GIS technique is used for airport surface management to study the optimization of airplane taxiway for arrival and departure flights. The shortest paths are designed for just-arrived and ready-for-departing flights of the airport. Additionally, whether the flights could confront each other head-to-head on the taxiway is judged. In regard to the airport′s security and efficiency, airplanes must continuously taxi along the shortest route and the head-to-head confrontation should not occur. Two schemes are designed: One is to change the taxiing velocity of arrival flights, the other is to delay the starting time of departure flights. This algorithm is approved by a practical example.

Global optimal path planning for mobile robot based onimproved Dijkstra algorithm and ant system algorithm

A novel method of global optimal path planning for mobile robot was proposed based on the improved Dijkstra algorithm and ant system algorithm. This method includes three steps: the first step is adopting the MAKLINK graph theory to establish the free space model of the mobile robot, the second step is adopting the improved Dijkstra algorithm to find out a sub-optimal collision-free path, and the third step is using the ant system algorithm to adjust and optimize the location of the sub-optimal path so as to generate the global optimal path for the mobile robot. The computer simulation experiment was carried out and the results show that this method is correct and effective. The comparison of the results confirms that the proposed method is better than the hybrid genetic algorithm in the global optimal path planning.

Path Planning and Tracking for Vehicle Parallel Parking Based on Preview BP Neural Network PID Controller

In order to diminish the impacts of extemal disturbance such as parking speed fluctuation and model un- certainty existing in steering kinematics, this paper presents a parallel path tracking method for vehicle based on pre- view back propagation （BP） neural network PID controller. The forward BP neural network can adjust the parameters of PID controller in real time. The preview time is optimized by considering path curvature, change in curvature and road boundaries. A fuzzy controller considering barriers and different road conditions is built to select the starting po- sition. In addition, a kind of path planning technology satisfying the requirement of obstacle avoidance is introduced. In order to solve the problem of discontinuous curvature, cubic B spline curve is used for curve fitting. The simulation results and real vehicle tests validate the effectiveness of the proposed path planning and tracking methods.

Application of GA, PSO, and ACO Algorithms to Path Planning of Autonomous Underwater Vehicles

In this paper, an underwater vehicle was modeled with six dimensional nonlinear equations of motion, controlled by DC motors in all degrees of freedom. Near-optimal trajectories in an energetic environment for underwater vehicles were computed using a nnmerical solution of a nonlinear optimal control problem （NOCP）. An energy performance index as a cost function, which should be minimized, was defmed. The resulting problem was a two-point boundary value problem （TPBVP）. A genetic algorithm （GA）, particle swarm optimization （PSO）, and ant colony optimization （ACO） algorithms were applied to solve the resulting TPBVP. Applying an Euler-Lagrange equation to the NOCP, a conjugate gradient penalty method was also adopted to solve the TPBVP. The problem of energetic environments, involving some energy sources, was discussed. Some near-optimal paths were found using a GA, PSO, and ACO algorithms. Finally, the problem of collision avoidance in an energetic environment was also taken into account.

Optimal path planning method of electric vehicles considering power supply

Because of the limitations of electric vehicle(EV)battery technology and relevant supporting facilities,there is a great risk of breakdown of EVs during driving.The resulting driver“range anxiety”greatly affects the travel quality of EVs.These limitations should be overcome to promote the use of EVs.In this study,a method for travel path planning considering EV power supply was developed.First,based on real-time road conditions,a dynamic energy model of EVs was established considering the driving energy and accessory energy.Second,a multi-objective travel path planning model of EVs was constructed considering the power supply,taking the distance,time,energy,and charging cost as the optimization objectives.Finally,taking the actual traffic network of 15 km×15 km area in a city as the research object,the model was simulated and verified in MATLAB based on Dijkstra shortest path algorithm.The simulation results show that compared with the traditional route planning method,the total distance in the proposed optimal route planning method increased by 1.18%,but the energy consumption,charging cost,and driving time decreased by 11.62%,41.26%and 11.00%,respectively,thus effectively reducing the travel cost of EVs and improving the driving quality of EVs.

Mobile robot path planning based on adaptive bacterial foraging algorithm

The utilization of biomimicry of bacterial foraging strategy was considered to develop an adaptive control strategy for mobile robot, and a bacterial foraging approach was proposed for robot path planning. In the proposed model, robot that mimics the behavior of bacteria is able to determine an optimal collision-free path between a start and a target point in the environment surrounded by obstacles. In the simulation, two test scenarios of static environment with different number obstacles were adopted to evaluate the performance of the proposed method. Simulation results show that the robot which reflects the bacterial foraging behavior can adapt to complex environments in the planned trajectories with both satisfactory accuracy and stability.