scholarly journals Global and Local Path Planning Study in a ROS-Based Research Platform for Autonomous Vehicles

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Pablo Marin-Plaza ◽  
Ahmed Hussein ◽  
David Martin ◽  
Arturo de la Escalera
Keyword(s):  
Path Planning ◽  
Autonomous Vehicles ◽  
Starting Point ◽  
Model Configuration ◽  
Software Prototyping ◽  
Research Platform ◽  
Local Path ◽  
Low Sensitivity ◽  
Global And Local ◽  
Carlos Iii

The aim of this work is to integrate and analyze the performance of a path planning method based on Time Elastic Bands (TEB) in real research platform based on Ackermann model. Moreover, it will be proved that all modules related to the navigation can coexist and work together to achieve the goal point without any collision. The study is done by analyzing the trajectory generated from global and local planners. The software prototyping tool is Robot Operating System (ROS) from Open Source Robotics Foundation and the research platform is the iCab (Intelligent Campus Automobile) from University Carlos III. This work has been validated from a test inside the campus where the iCab has performed the navigation between the starting point and the goal point without any collision. During the experiment, we proved the low sensitivity of the TEB method to variations of the vehicle model configuration and constraints.

A joint global and local path planning optimization for UAV task scheduling towards crowd air monitoring

2021 ◽  
Vol 193 ◽  
pp. 107913
Author(s):  
Yuan Tang ◽  
Yiming Miao ◽  
Ahmed Barnawi ◽  
Bander Alzahrani ◽  
Reem Alotaibi ◽  
...  
Keyword(s):  
Path Planning ◽  
Task Scheduling ◽  
Air Monitoring ◽  
Local Path Planning ◽  
Planning Optimization ◽  
Local Path ◽  
Global And Local

scholarly journals Path Planning for Autonomous Ships: A Hybrid Approach Based on Improved APF and Modified VO Methods

2021 ◽  
Vol 9 (7) ◽  
pp. 761
Author(s):  
Liang Zhang ◽  
Junmin Mou ◽  
Pengfei Chen ◽  
Mengxia Li
Keyword(s):  
Path Planning ◽  
Local Minimum ◽  
Hybrid Approach ◽  
Artificial Potential Field ◽  
Whole Process ◽  
International Regulations ◽  
Local Path ◽  
Velocity Obstacle ◽  
Global And Local

In this research, a hybrid approach for path planning of autonomous ships that generates both global and local paths, respectively, is proposed. The global path is obtained via an improved artificial potential field (APF) method, which makes up for the shortcoming that the typical APF method easily falls into a local minimum. A modified velocity obstacle (VO) method that incorporates the closest point of approach (CPA) model and the International Regulations for Preventing Collisions at Sea (COLREGS), based on the typical VO method, can be used to get the local path. The contribution of this research is two-fold: (1) improvement of the typical APF and VO methods, making up for previous shortcomings, and integrated COLREGS rules and good seamanship, making the paths obtained more in line with navigation practice; (2) the research included global and local path planning, considering both the safety and maneuverability of the ship in the process of avoiding collision, and studied the whole process of avoiding collision in a relatively entirely way. A case study was then conducted to test the proposed approach in different situations. The results indicate that the proposed approach can find both global and local paths to avoid the target ship.

scholarly journals Path Planning Methods in an Environment with Obstacles (A Review)

2018 ◽  
pp. 15-58 ◽  
Author(s):  
W. Liu
Keyword(s):  
Path Planning ◽  
Incomplete Information ◽  
Cell Decomposition ◽  
Reference Points ◽  
Mobile Robot Navigation ◽  
Problem Solution ◽  
Local Path Planning ◽  
Starting Point ◽  
Planning Methods ◽  
Local Path

Planning the path is the most important task in the mobile robot navigation. This task involves basically three aspects. First, the planned path must run from a given starting point to a given endpoint. Secondly, it should ensure robot’s collision-free movement. Thirdly, among all the possible paths that meet the first two requirements it must be, in a certain sense, optimal.Methods of path planning can be classified according to different characteristics. In the context of using intelligent technologies, they can be divided into traditional methods and heuristic ones. By the nature of the environment, it is possible to divide planning methods into planning methods in a static environment and in a dynamic one (it should be noted, however, that a static environment is rare). Methods can also be divided according to the completeness of information about the environment, namely methods with complete information (in this case the issue is a global path planning) and methods with incomplete information (usually, this refers to the situational awareness in the immediate vicinity of the robot, in this case it is a local path planning). Note that incomplete information about the environment can be a consequence of the changing environment, i.e. in a dynamic environment, there is, usually, a local path planning.Literature offers a great deal of methods for path planning where various heuristic techniques are used, which, as a rule, result from the denotative meaning of the problem being solved. This review discusses the main approaches to the problem solution. Here we can distinguish five classes of basic methods: graph-based methods, methods based on cell decomposition, use of potential fields, optimization methods, фтв methods based on intelligent technologies.Many methods of path planning, as a result, give a chain of reference points (waypoints) connecting the beginning and end of the path. This should be seen as an intermediate result. The problem to route the reference points along the constructed chain arises. It is called the task of smoothing the path, and the review addresses this problem as well.

Optimization of Focused Wave Front Algorithm in Unknown Dynamic Environment for Multi-Robot Navigation

2013 ◽  
Vol 3 (4) ◽  
pp. 1-29
Author(s):  
Priyanka Meel ◽  
Ritu Tiwari ◽  
Anupam Shukla
Keyword(s):  
Path Planning ◽  
Wave Front ◽  
Dynamic Environment ◽  
New Method ◽  
Safety Zone ◽  
Color Sensitivity ◽  
Focused Wave ◽  
Local Path ◽  
Global And Local ◽  
Multi Robot

Robotics is a field which includes multiple disciplines such as environment mapping, localization, path planning, path execution, area exploration etc. Path planning is the elementary requirement for all the above mentioned diversified fields. This paper presents a new method for motion planning of mobile robots which carry forward the best features of Focused Wave Front and other wave front based path planners, at the same time optimizes the algorithm in terms of path length, energy consumption and memory requirements. This research introduces a method of choosing every next step in grid based environment and also proposes a backtracking procedure to minimize turns by means of identifying landmark points in the path. Further, the authors have enhanced the functionality of Focused Wave Front algorithm by applying it in uncertain dynamic environment. The proposed method is a combination of global and local path planning as well as online and offline navigation process. A new method based on bidirectional wave propagation along the walls of obstacle and wall following behavior is being proposed for avoiding uncertain static obstacles. Considering the criticalness of moving obstacles a colored safety zone is assumed to have around them and the robot is equipped with color sensitivity. Based on the particular color (red, green, yellow) that has sensed the robot will make intelligent decisions to avoid them. The simulation result reflects how the proposed method has efficiently and safely navigates a robot towards its destination by avoiding all known and unknown obstacles. Finally the algorithms are extended for multi-robot environment.

Optimization of Focused Wave Front Algorithm in Unknown Dynamic Environment for Multi-Robot Navigation

2019 ◽  
pp. 553-581
Author(s):  
Priyanka Meel ◽  
Ritu Tiwari ◽  
Anupam Shukla
Keyword(s):  
Path Planning ◽  
Wave Front ◽  
Path Length ◽  
Dynamic Environment ◽  
New Method ◽  
Focused Wave ◽  
Local Path ◽  
Global And Local ◽  
Grid Based ◽  
Multi Robot

Robotics is a field which includes multiple disciplines such as environment mapping, localization, path planning, path execution, area exploration etc. Path planning is the elementary requirement for all the above mentioned diversified fields. This paper presents a new method for motion planning of mobile robots which carry forward the best features of Focused Wave Front and other wave front based path planners, at the same time optimizes the algorithm in terms of path length, energy consumption and memory requirements. This research introduces a method of choosing every next step in grid based environment and also proposes a backtracking procedure to minimize turns by means of identifying landmark points in the path. Further, the authors have enhanced the functionality of Focused Wave Front algorithm by applying it in uncertain dynamic environment. The proposed method is a combination of global and local path planning as well as online and offline navigation process. A new method based on bidirectional wave propagation along the walls of obstacle and wall following behavior is being proposed for avoiding uncertain static obstacles. Considering the criticalness of moving obstacles a colored safety zone is assumed to have around them and the robot is equipped with color sensitivity. Based on the particular color (red, green, yellow) that has sensed the robot will make intelligent decisions to avoid them. The simulation result reflects how the proposed method has efficiently and safely navigates a robot towards its destination by avoiding all known and unknown obstacles. Finally the algorithms are extended for multi-robot environment.

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