Visibility-based UAV path planning for surveillance in cluttered environments

2014 ◽  
Author(s):  
Vengatesan Govindaraju ◽  
Gerard Leng ◽  
Zhang Qian
Keyword(s):  
Path Planning ◽  
Cluttered Environments

A survey on the application of path-planning algorithms for multi-rotor UAVs in precision agriculture

2022 ◽  
pp. 1-20
Author(s):  
Amin Basiri ◽  
Valerio Mariani ◽  
Giuseppe Silano ◽  
Muhammad Aatif ◽  
Luigi Iannelli ◽  
...  
Keyword(s):  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Flight Control ◽  
Precision Agriculture ◽  
Navigation Systems ◽  
Agricultural Crops ◽  
Cluttered Environments ◽  
Main Motivation ◽  
Autonomous Guidance ◽  
Planning Problems

Abstract Multi-rotor Unmanned Aerial Vehicles (UAVs), although originally designed and developed for defence and military purposes, in the last ten years have gained momentum, especially for civilian applications, such as search and rescue, surveying and mapping, and agricultural crops and monitoring. Thanks to their hovering and Vertical Take-Off and Landing (VTOL) capabilities and the capacity to carry out tasks with complete autonomy, they are now a standard platform for both research and industrial uses. However, while the flight control architecture is well established in the literature, there are still many challenges in designing autonomous guidance and navigation systems to make the UAV able to work in constrained and cluttered environments or also indoors. Therefore, the main motivation of this work is to provide a comprehensive and exhaustive literature review on the numerous methods and approaches to address path-planning problems for multi-rotor UAVs. In particular, the inclusion of a review of the related research in the context of Precision Agriculture (PA) provides a unified and accessible presentation for researchers who are initiating their endeavours in this subject.

Planning the Shortest Path in Cluttered Environments: A Review and a Planar Convex Hull-Based Approach

2019 ◽  
Vol 19 (4) ◽  
Author(s):  
Nafiseh Masoudi ◽  
Georges M. Fadel ◽  
Margaret M. Wiecek
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Time Complexity ◽  
Optimal Path ◽  
Optimal Solution ◽  
Free Graph ◽  
Worst Case ◽  
Cluttered Environments ◽  
Planar Convex ◽  
Polyhedral Obstacles

Abstract Routing or path-planning is the problem of finding a collision-free and preferably shortest path in an environment usually scattered with polygonal or polyhedral obstacles. The geometric algorithms oftentimes tackle the problem by modeling the environment as a collision-free graph. Search algorithms such as Dijkstra’s can then be applied to find an optimal path on the created graph. Previously developed methods to construct the collision-free graph, without loss of generality, explore the entire workspace of the problem. For the single-source single-destination planning problems, this results in generating some unnecessary information that has little value and could increase the time complexity of the algorithm. In this paper, first a comprehensive review of the previous studies on the path-planning subject is presented. Next, an approach to address the planar problem based on the notion of convex hulls is introduced and its efficiency is tested on sample planar problems. The proposed algorithm focuses only on a portion of the workspace interacting with the straight line connecting the start and goal points. Hence, we are able to reduce the size of the roadmap while generating the exact globally optimal solution. Considering the worst case that all the obstacles in a planar workspace are intersecting, the algorithm yields a time complexity of O(n log(n/f)), with n being the total number of vertices and f being the number of obstacles. The computational complexity of the algorithm outperforms the previous attempts in reducing the size of the graph yet generates the exact solution.

A local-based method for manipulators path planning, using sub-goals resulting from a local graph

Robotica ◽  
2006 ◽  
Vol 24 (5) ◽  
pp. 539-548 ◽  
Author(s):  
S. Zeghloul ◽  
C. Helguera ◽  
G. Ramirez
Keyword(s):  
Path Planning ◽  
Local Environment ◽  
Linear Constraints ◽  
Geometric Constraints ◽  
Planning Problem ◽  
Cluttered Environments ◽  
Free Position ◽  
Local Methods ◽  
Path Planner ◽  
Path Planning Problem

This paper addresses the path planning problem for manipulators. The problem of path planning in robotics can be defined as follows: To find a collision free trajectory from an initial configuration to a goal configuration. In this paper a collision-free path planner for manipulators, based on a local constraints method, is proposed. In this approach the task is described by a minimization problem under geometric constraints. The anti-collision constraints are mapped as linear constraints in the configuration space and they are not included in the function to minimize. Also, the task to achieve is defined as a combination of two displacements. The first displacement brings the robot towards to the goal configuration, while the second one allows the robot to avoid the local minima. This formulation solves many of classical problems found in local methods. However, when the robot acts in some heavy cluttered environments, a zig-zaging phenomenon could appear. To solve this situation, a graph based on the local environment of the robot is constructed. On this graph, an A* search is performed, in order to find a dead-lock free position that can be used as a sub-goal in the optimization process. This path-planner has been implemented within SMAR, a CAD-Robotics system developed at our laboratory. Tests in heavy cluttered environments were successfully performed.

Path Planning for Manipulator Robots in Cluttered Environments

2005 ◽  
Author(s):  
Samir Lahouar ◽  
Said Zeghloul ◽  
Lotfi Romdhane
Keyword(s):  
Path Planning ◽  
Shortest Path ◽  
Planning Method ◽  
Search Process ◽  
Grid Cells ◽  
Heuristic Function ◽  
Search Mode ◽  
Cluttered Environments ◽  
Grid Sampling ◽  
Cluttered Environment

In this paper we propose a new path planning method for robot manipulators in cluttered environments, based on lazy grid sampling. Grid cells are built while searching for the path to the goal configuration. The proposed planner acts in two modes. A depth mode, while the robot is far from obstacles, makes it evolve toward its goal. While a width search mode becomes active when the robot gets close to an obstacle. This method provides the shortest path to go around the obstacle. It also reduces the gap between pre-computed grid methods and lazy grid methods. No heuristic function is needed to guide the search process. An example dealing with a robot in a cluttered environment is presented to show the efficiency of the method.

scholarly journals Multi UAV Coverage Path Planning in Urban Environments

Sensors ◽  
2021 ◽  
Vol 21 (21) ◽  
pp. 7365
Author(s):  
Javier Muñoz ◽  
Blanca López ◽  
Fernando Quevedo ◽  
Concepción A. Monje ◽  
Santiago Garrido ◽  
...  
Keyword(s):  
Path Planning ◽  
Collision Avoidance ◽  
Urban Environments ◽  
Fast Marching ◽  
Flight Pattern ◽  
Cluttered Environments ◽  
Coverage Path Planning ◽  
Area Of Interest ◽  
Smooth Path ◽  
Multi Uav

Coverage path planning (CPP) is a field of study which objective is to find a path that covers every point of a certain area of interest. Recently, the use of Unmanned Aerial Vehicles (UAVs) has become more proficient in various applications such as surveillance, terrain coverage, mapping, natural disaster tracking, transport, and others. The aim of this paper is to design efficient coverage path planning collision-avoidance capable algorithms for single or multi UAV systems in cluttered urban environments. Two algorithms are developed and explored: one of them plans paths to cover a target zone delimited by a given perimeter with predefined coverage height and bandwidth, using a boustrophedon flight pattern, while the other proposed algorithm follows a set of predefined viewpoints , calculating a smooth path that ensures that the UAVs pass over the objectives. Both algorithms have been developed for a scalable number of UAVs, which fly in a triangular deformable leader-follower formation with the leader at its front. In the case of an even number of UAVs, there is no leader at the front of the formation and a virtual leader is used to plan the paths of the followers. The presented algorithms also have collision avoidance capabilities, powered by the Fast Marching Square algorithm. These algorithms are tested in various simulated urban and cluttered environments, and they prove capable of providing safe and smooth paths for the UAV formation in urban environments.

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