3D Path Planning for Quadrotor Using Gazebo Simulator

2019 ◽  
Vol 2 (3) ◽  
pp. 200-205
Author(s):  
Mohammad Ryan Dirgantara ◽  
Eka Budiarto ◽  
Rusman Rusyadi
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Robot Operating System ◽  
Physical Prototype ◽  
Set Up

This research explores the 3D path planning for quadrotor, which is an unmannedaerial vehicle (UAV) with four rotors. The quadrotor is simulated using robot operating system(ROS) and Gazebo software, and is equipped with camera, GPS sensor, and inertialmeasurement unit (IMU) sensor to do the mapping of its environment. The packages used inROS are Hector Quadrotor package, joystick package, Octomap package, and MoveIt package.These packages were modified so that it could be integrated with each other and fulfill theobjective of this research. For the 3D path planning, a method called rapidly-exploring randomtree (RRT) is explored and implemented. Several experiments regarding the behavior of thequadrotor, the mapping, and the path planning were conducted to find out the performance andlimitations of the simulation. This simulation is set up so that it can be used to validate a newdesign of quadrotor before it is tested with a physical prototype.

CPC Algorithm: Exact Area Coverage by a Mobile Robot Using Approximate Cellular Decomposition

Robotica ◽  
2020 ◽  
pp. 1-22
Author(s):  
K. R. Guruprasad ◽  
T. D. Ranjitha
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Mobile Robot ◽  
Formal Analysis ◽  
Area Coverage ◽  
Cell Permeability ◽  
Cellular Decomposition ◽  
Robot Operating System ◽  
Coverage Path Planning

SUMMARY A new coverage path planning (CPP) algorithm, namely cell permeability-based coverage (CPC) algorithm, is proposed in this paper. Unlike the most CPP algorithms using approximate cellular decomposition, the proposed algorithm achieves exact coverage with lower coverage overlap compared to that with the existing algorithms. Apart from a formal analysis of the algorithm, the performance of the proposed algorithm is compared with two representative approximate cellular decomposition-based coverage algorithms reported in the literature. Results of demonstrative experiments on a TurtleBot mobile robot within the robot operating system/Gazebo environment and on a Fire Bird V robot are also provided.

Autonomous Exploration and Inspection Path Planning for Aerial Robots Using the Robot Operating System

2018 ◽  
pp. 67-111 ◽  
Author(s):  
Christos Papachristos ◽  
Mina Kamel ◽  
Marija Popović ◽  
Shehryar Khattak ◽  
Andreas Bircher ◽  
...  
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Autonomous Exploration ◽  
Robot Operating System ◽  
Aerial Robots

scholarly journals A web application for remote control of ROS robot based on WebSocket protocol and Django development environment

2021 ◽  
Vol 1208 (1) ◽  
pp. 012035
Author(s):  
Zinaid Kapić ◽  
Aladin Crnkić ◽  
Edin Mujčić ◽  
Jasna Hamzabegović
Keyword(s):  
Operating System ◽  
Remote Control ◽  
Path Planning ◽  
Experimental Work ◽  
Web Application ◽  
Web Interface ◽  
Development Environment ◽  
Work Analysis ◽  
Robot Operating System ◽  
Teleoperation Systems

Abstract The development of teleoperation systems, robots, or any physical part of the system can be costly and if something goes wrong it can lead to development overdue. Precisely for these reasons, engineers and scientists today resort to the development of simulated systems before the construction of a real system. Robot Operating System (ROS) is one of the most popular solutions for robot development, manipulation, and simulation. In this paper, we present a web application for remote control of a ROS robot. The robot is controlled via a web application that is used as a virtual Joystick. Also, in this paper, an experimental work analysis of the projected system is performed. Further research possibilities include upgrading the presented web interface, adding certain motion autonomy sensors, or integrating some path planning algorithms.

scholarly journals Hardware in the Loop Topology for an Omnidirectional Mobile Robot Using Matlab in a Robot Operating System Environment

Symmetry ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 969
Author(s):  
Constantin-Catalin Dosoftei ◽  
Alexandru-Tudor Popovici ◽  
Petru-Razvan Sacaleanu ◽  
Paul-Marcelin Gherghel ◽  
Cristina Budaciu
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Mobile Robot ◽  
Autonomous Navigation ◽  
Vertical Axis ◽  
Hardware In The Loop ◽  
Robot Operating System ◽  
System Nodes ◽  
Navigation Software ◽  
Time Autonomous

The symmetry of the omnidirectional robot motion abilities around its central vertical axis is an important advantage regarding its driveability for the flexible interoperation with fixed conveyor systems. The paper illustrates a Hardware in the Loop architectural approach for integrated development of an Ominidirectional Mobile Robot that is designed to serve in a dynamic logistic environment. Such logistic environments require complex algorithms for autonomous navigation between different warehouse locations, that can be efficiently developed using Robot Operating System nodes. Implementing path planning nodes benefits from using Matlab-Simulink, which provides a large selection of algorithms that are easily integrated and customized. The proposed solution is deployed for validation on a NVIDIA Jetson Nano, the embedded computer hosted locally on the robot, that runs the autonomous navigation software. The proposed solution permits the live connection to the omnidirectional prototype platform, allowing to deploy algorithms and acquire data for debugging the location, path planning and the mapping information during real time autonomous navigation experiments, very useful in validating different strategies.

scholarly journals Path Planning Based on Improved Hybrid A* Algorithm

2021 ◽  
Vol 25 (1) ◽  
pp. 64-72
Author(s):  
Bijun Tang ◽  
◽  
Kaoru Hirota ◽  
Xiangdong Wu ◽  
Yaping Dai ◽  
...  
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Mobile Robots ◽  
Potential Field ◽  
Artificial Potential Field ◽  
A Algorithm ◽  
Ground Vehicle ◽  
Holonomic Constraints ◽  
Robot Operating System ◽  
Maximum Curvature

Hybrid A* algorithm has been widely used in mobile robots to obtain paths that are collision-free and drivable. However, the outputs of hybrid A* algorithm always contain unnecessary steering actions and are close to the obstacles. In this paper, the artificial potential field (APF) concept is applied to optimize the paths generated by the hybrid A* algorithm. The generated path not only satisfies the non-holonomic constraints of the vehicle, but also is smooth and keeps a comfortable distance to the obstacle at the same time. Through the robot operating system (ROS) platform, the path planning experiments are carried out based on the hybrid A* algorithm and the improved hybrid A* algorithm, respectively. In the experiments, the results show that the improved hybrid A* algorithm greatly reduces the number of steering actions and the maximum curvature of the paths in many different common scenarios. The paths generated by the improved algorithm nearly do not have unnecessary steering or sharp turning before the obstacles, which are safer and smoother than the paths generated by the hybrid A* algorithm for the autonomous ground vehicle.

scholarly journals Path Planning and Obstacle Avoidance for UAV in an Uncharted Environment

2021 ◽  
Vol 9 (8) ◽  
pp. 2353-2359
Author(s):  
Shubhankar Goje
Keyword(s):  
Operating System ◽  
Path Planning ◽  
Unmanned Aerial Vehicles ◽  
Obstacle Avoidance ◽  
Obstacle Detection ◽  
Ongoing Research ◽  
Robot Operating System ◽  
Aerial Vehicles ◽  
Different Types ◽  
Infinite Loop

Abstract: The growing industry of unmanned aerial vehicles (UAV) requires an efficient and robust algorithm to decide the path of the UAV and avoid obstacles. The study of pathfinding algorithms is ongoing research not just useful in the domain of drones, but in other fields like video games (AI pathfinding), terrain traversal (mapped, unmapped, areal, underwater, land, etc.), and industries that require robots to deliver packages. This paper proposes a new pathfinding algorithm that aims to solve the problem of pathfinding in unknown 2-dimensional terrain. Based on a system of assumptions and using the help of a set of sensors aboard the UAV, the algorithm navigates the UAV from a start point to an endpoint while avoiding any shape or size of obstacles in between. To avoid multiple different types of “infinite loop” situations where the UAV gets stuck around an obstacle, a priority-based selector for intermediate destinations is created. The algorithm is found to work effectively when simulated in Gazebo on Robot Operating System (ROS). Keywords: Path Planning, UAV, Obstacle Avoidance, Drone Navigation, Obstacle Detection, Uncharted Environment.

F1_Tenth_Course_Report_Group_C

2018 ◽  
Author(s):  
Yi Chen ◽  
Sagar Manglani ◽  
Roberto Merco ◽  
Drew Bolduc
Keyword(s):  
Operating System ◽  
Autonomous Driving ◽  
Software Tools ◽  
Simulation Environment ◽  
Robot Operating System ◽  
Available Information

In this paper, we discuss several of major robot/vehicle platforms available and demonstrate the implementation of autonomous techniques on one such platform, the F1/10. Robot Operating System was chosen for its existing collection of software tools, libraries, and simulation environment. We build on the available information for the F1/10 vehicle and illustrate key tools that will help achieve properly functioning hardware. We provide methods to build algorithms and give examples of deploying these algorithms to complete autonomous driving tasks and build 2D maps using SLAM. Finally, we discuss the results of our findings and how they can be improved.

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