Shortest Path Planning Research Articles

Formation Vector Based Shortest Path-Planning in CGF Formation

In order to improve the poor reality and bad flexibility of the mapping relationship which matched entities with aim locations in traditional approximation method, the formation vector shortest path-planning method was presented in this paper. By analyzing the lack of aim path-planning in the approximation method, shortest path-planning was discussed and was improved by introducing the formation vector and the idea of pheromone. Furthermore, the improved algorithm was applied in a CGF simulation system. The experimental results showed that the mapping relationship had better reality and rationality and the possibility of collision was significantly reduced than the traditional formation change process.

Robot Global Path Planning Based on Improved Artificial Fish-Swarm Algorithm

In This study, a new artificial fish-swarm optimization, to improve the foraging behavior of artificial fish swarm algorithm is closer to reality in order to let the fish foraging behavior, increase a look at the link (search) ambient, after examining environment, artificial fish can get more status information of the surrounding environment. Artificial fish screened from the information obtained optimal state for the best direction of movement. Will improve the foraging behavior of artificial fish-swarm algorithm applied to robot global path planning, including the robot to bypass the analog obstacles selected three ways: go obstructions outside, go inside the obstacles, both away obstructions and went outside obstacles Thing achieve robot shortest path planning. Via the MATLAB software emulation test: the improved foraging behavior of artificial fish-swarm algorithm to improve the rapid convergence of the algorithm and stability, improve fish swarm algorithm to the adaptability of the robot global path planning.

The Shortest Path Planning for Manoeuvres of UAV

It is important to find the shortest path for manoeuvres of UAV, since the power consumed during manoeuvres is tightly coupled with the length of the flight path. In this paper, an algorithm that can find the shortest path during manoeuvres and improve the performance of UAV to follow waypoints is described. The shortest path for UAV during manoeuvres is derived firstly by the theory of Dubins curve. Secondly, in order to improve the ability of UAV to follow the derived optimal path, a real-time path planning algorithm is designed by transforming the constraints of Dubins curve into a dynamic equation. To demonstrate the applicability and performance of the proposed path planning algorithm, two numerical examples are presented. The results show that the proposed algorithm is promising to be applied in the path planning for manoeuvres of UAV.

On the Shortest and Conflict-Free Path Planning of Multi-AGV System Based on Dijkstra Algorithm and the Dynamic Time-Window Method

This paper presents a dynamic routing method for shortest path planning and conflict prevention of AGV system, and then illustrates the principle and implementation of this method. It gives a way to schedule a shortest and conflict-free route by utilizing Dijkstra algorithm and the Dynamic Time-Window Method, and comes to the conclusion by experiments that the combination of these algorithms will solve the routing problem of small-sized multi-AGV system to a large extent.

Take Me to the Bus Stop: AR Based Assistance System for Public Transit Users

Route bus system is the fundamental public transporta- tion system and has an important role in every province. To improve the usability of it greatly, we develop an AR application for Bus- Net. The Bus-Net system is the shortest path planning system. Bus-Net supports bus users to make a plan to change buses by providing them with information about the direction. However, with Bus-Net, these information are provided in text-base. It is difficult to understand them for the person who does not know the place. We developed the AR application for Bus-Net. It supports the action of a bus user in an innovative way by putting information on a camera picture and leading the way to a bus stop. The application also inform the user the correct bus to get, the direction the bus takes and the fare, which ease many anxieties and worries people tend to feel when they take buses.

Path planning for mobile robot in a 2.5‐dimensional grid‐based map

PurposeTwo and one half‐dimensional (2.5D) grid maps are useful for navigation in outdoor environment or on non‐flat surface. However, little attention has been given to how to find an optimal path in a 2.5D grid map. The purpose of this paper is to develop a path‐planning method in a 2.5D grid map, which aims to provide an efficient solution to robot path planning no matter whether the robot is equipped with the prior knowledge of the environment.Design/methodology/approachA 2.5D grid representation is proposed to model non‐flat surface for mobile robots. According to the graph extracted from the 2.5D grid map, an improved searching approach derived from A* algorithm is presented for the shortest path planning. With reasonable assumption, the approach is improved for the path planning in unknown environment.FindingsIt is confirmed by experiments that the proposed planning approach provide a solution to the problem of optimal path planning in 2.5 grid maps. Furthermore, the experiment results demonstrate that our 2.5D D* method leads to more efficient dynamic path planning for navigation in unknown environment.Originality/valueThis paper proposes a path‐planning approach in a 2.5D grid map which is used to represent a non‐flat surface. The approach is capable of efficient navigation no matter whether the global environmental information is available at the beginning of exploration.

Fuzzy Path Planning In A Plane With Stationary Obstacles

In this paper a new approach for finding optimal path planning in a plane with stationary obstacles is discussed. At first, we consider a movable rigid object in a plane with stationary obstacles. The goal is to find the shortest path planning which brings rigid object from a given initial point to a given final point such that the length of path be minimized and distance between object and obstacles be maximized. By considering the length of path and the distance between rigid object with obstacles as objective functions, we obtain a multi-objective problem. Because of the imprecise nature of decision maker's judgment, these multiple objectives are viewed as fuzzy variables. Then we determine intervals for the value of objective functions such that these intervals for the distance between rigid object and obstacles are given by decision maker, and for the length of path is achieved by solving two optimal nonlinear problems (ONP). Now, we define a decreasing or increasing membership function for any objective functions on achieved intervals. Then the optimal policy is to find an optimal path which maximize all of membership functions, simultaneously. After a little calculation, we obtain an ONP. By solving this ONP, a (local) Pareto optimal solution for original goal is attained. Numerical example is also given.

Shortest Path Planning Strategies through Evolutionary Algorithms

Shortest Path Planning Strategies through Evolutionary Algorithms

Prune-Able Fuzzy ART Neural Architecture for Robot Map Learning and Navigation in Dynamic Environments

Mobile robots must be able to build their own maps to navigate in unknown worlds. Expanding a previously proposed method based on the fuzzy ART neural architecture (FARTNA), this paper introduces a new online method for learning maps of unknown dynamic worlds. For this purpose the new Prune-able fuzzy adaptive resonance theory neural architecture (PAFARTNA) is introduced. It extends the FARTNA self-organizing neural network with novel mechanisms that provide important dynamic adaptation capabilities. Relevant PAFARTNA properties are formulated and demonstrated. A method is proposed for the perception of object removals, and then integrated with PAFARTNA. The proposed methods are integrated into a navigation architecture. With the new navigation architecture the mobile robot is able to navigate in changing worlds, and a degree of optimality is maintained, associated to a shortest path planning approach implemented in real-time over the underlying global world model. Experimental results obtained with a Nomad 200 robot are presented demonstrating the feasibility and effectiveness of the proposed methods.

Three-dimensional Euclidean distance transformation and its application to shortest path planning

In this paper, we present a novel method to obtain the three-dimensional Euclidean distance transformation (EDT) in two scans of the image. The shortest path can be extracted based on the distance maps using the minimum value tracing. The EDT is obtained correctly and efficiently in a constant time for arbitrary types of images, including the existence of obstacles. By adopting the new dynamically rotational mathematical morphology, we not only guarantee the collision-free in the shortest path, but also reduce the time complexity dramatically.

Navigation of a mobile robot by locally optimal trajectories

This paper proposes a navigation system for a non-holonomic mobile robot. The navigation is based on a “look and move” approach. The aim is to define intermediate points called sub-goals through which the robot must pass. This algorithm is particularly suitable for navigation in an unknown environment and obstacle avoidance. Between two successive sub-goals, a shortest path planning solution is adopted. We have adopted the “Dubins' car” because of the environment perception sensor, a 180° laser scanner. In order to minimize the calculation time, the theoretical results of shortest path are approximated by simple equations. The navigation algorithm proposed can be used either in a structured or unstructured environment. In this context the local map construction is based on the segmentation of a structured environment; so for an unstructured environment, a suitable algorithm must be used instead.

Shortest path planning on topographical maps

This paper introduces a new algorithm for quickly answering repetitive least-cost queries between pairs of points on the Earth's surface as represented by digital topographical maps. The algorithm uses a three-step process; preprocessing, geometrically modified Dijkstra search, and postprocessing. The preprocessing step computes and saves highly valuable global information that describes the underlying geometry of the terrain. The search step solves shortest path queries using a modified Dijkstra algorithm that takes advantage of the preprocessed information to "jump" quickly across flat terrain and decide whether a path should go over or through a high-cost region. The final step is a path improvement process that straightens and globally improves the path. Our algorithm partitions the search space into free regions and obstacle regions. However, unlike other algorithms using this approach, our algorithm keeps the option of passing through an obstacle region.

A morphological approach to shortest path planning for rotating objects

This paper presents a mathematical morphology based approach to find the shortest path of an arbitrarily shaped moving object with rotations amid obstacles of arbitrary shapes. By utilizing the proposed rotational morphology along with the continuous turning-angle constraint, the representation framework of the motion planning problem becomes simple and practical. Two vehicle models with different driving and turning systems are used in solving the path planning problem and their strategies are presented. Simulation results show that our algorithm works successfully in various conditions.

Three-Dimensional Shortest Path Planning in the Presence of Polyhedral Obstacles

A new algorithm is presented for solving the three-dimensional shortest path planning (3DSP) problem for a point object moving among convex polyhedral obstacles. It is the first non-approximate three-dimensional path planing algorithm that can deal with more than two polyhedral obstacles. The algorithm extends the visibility graph concept from two dimensions to three dimensions. The two main problems with 3DSP are identifying the edge sequence the shortest path passes through and the turning points of the shortest path. A technique based on projective relationships is presented for identifying the set of visible boundary edges (VBE) corresponding to a given view point over which the shortest path, from the view point to the goal, will pass. VBE are used to construct an initial reduced visibility graph (RVG). Optimization is used to revise the position of the turning points and hence the three-dimensional RVG (3DRVG) and the global shortest path is then selected from the 3DRVG. The algorithm is of computational complexity O(n3vk), where n is the number of verticles, v is the maximum number of vertices on any one obstacle and k is the number of obstacles. The algorithm is applicable only with polyhedral obstacles, as the theorems developed for searching for the turning points of the three-dimensional shortest path are based on straight edges of the obstacles. It needs to be further developed for dealing with arbitrary-shaped obstacles and this would increase the computational complexity. The algorithm is tested using computer simulations and some results are presented.

A note on the combinatorial structure of the visibility graph in simple polygons

Combinatorial structure of visibility is probably one of the most fascinating and interesting areas of engineering and computer science. The usefulness of visibility graphs in computational geometry and robotic navigation problems like motion planning, unknown-terrain learning, shortest-path planning, etc., cannot be overstressed. The visibility graph, apart from being an important data structure for storing and updating geometric information, is a valuable mathematical tool in probing and understanding the nature of shapes of polygonal and polyhedral objects. In this research we wish to initially focus our attention on a fundamental class of geometric objects. These geometric objects may be looked upon as building blocks for more complex geometric objects, and which offer an ideal balance between complexity and simplicity, namely simple polygons. A major theme of the proposed paper is the investigation of the combinatorial structure of the visibility graph. More importantly, the goals of this paper are: 1. (i) To characterize the visibility graphs of simple polygons by obtaining necessary and sufficient conditions a graph must satisfy to qualify for the visibility graph of a simple polygon 2. (ii) To obtain hierarchical relationships between visibility graphs of simple polygons of a given number of vertices by treating them as representing simple polygons that are deformations of one another. 3. (iii) To exploit the potential of complete graphs to be natural coordinate systems for addressing the problem of reconstructing a simple polygon from visibility graph. We intend to achieve this by defining appropriate “betweenness” relationships on points with respect to the edges of the complete graphs.

Shortest path planning in discretized workspaces using dominance relation

A method of partitioning a workspace using rectilinear visibility in 3-D or higher space is presented. Unlike the case of 2-D space where the shape of a partition is a rectangle, the shape of a partition in 3-D or higher space is arbitrary. The existence of dominance relations between the partitioned regions is proven. This relation is then utilized to efficiently solve the shortest path planning problem in 3-D or higher space.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Contraction Mappings in the Theory Underlying Dynamic Programming

Contraction Mappings in the Theory Underlying Dynamic Programming