Optimal path planning of a disinfection mobile robot against COVID-19 in a ROS-based research platform

Due to COVID-19 pandemic, there is an increasing demand for mobile robots to substitute human in disinfection tasks. New generations of disinfection robots could be developed to navigate in high-risk, high-touch areas. Public spaces, such as airports, schools, malls, hospitals, workplaces and factories could benefit from robotic disinfection in terms of task accuracy, cost, and execution time. The aim of this work is to integrate and analyse the performance of Particle Swarm Optimization (PSO) algorithm, as global path planner, coupled with Dynamic Window Approach (DWA) for reactive collision avoidance using a ROS-based software prototyping tool. This paper introduces our solution – a SLAM (Simultaneous Localization and Mapping) and optimal path planning-based approach for performing autonomous indoor disinfection work. This ROS-based solution could be easily transferred to different hardware platforms to substitute human to conduct disinfection work in different real contaminated environments.

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Optimal Path Planning and Control of a Hexarotor with Mass Uncertainty in the Presence of Dynamic Obstacles and Wind Using Sliding Mode and Adaptive PSO Algorithm

10.1109/icee52715.2021.9544503 ◽

2021 ◽

Author(s):

Nima Sina ◽

Peyman Amiri ◽

Mohammad Danesh

Keyword(s):

Path Planning ◽

Sliding Mode ◽

Optimal Path ◽

Pso Algorithm ◽

Optimal Path Planning ◽

Planning And Control ◽

Adaptive Pso ◽

Mass Uncertainty ◽

And Control

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Autonomous Mobile Robot Navigation Based on PSO Algorithm with Inertia Weight Variants for Optimal Path Planning

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/928/2/022005 ◽

2020 ◽

Vol 928 ◽

pp. 022005

Author(s):

Tahseen Fadhel Abaas ◽

Alaa Hassan Shabeeb

Keyword(s):

Path Planning ◽

Mobile Robot ◽

Robot Navigation ◽

Optimal Path ◽

Pso Algorithm ◽

Mobile Robot Navigation ◽

Autonomous Mobile Robot ◽

Optimal Path Planning ◽

Inertia Weight

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Efficient Path Planning of Secondary Additive Manufacturing Operations

MATEC Web of Conferences ◽

10.1051/matecconf/201824903011 ◽

2018 ◽

Vol 249 ◽

pp. 03011

Author(s):

Keimargeo McQueen ◽

Sara Darensbourg ◽

Carl Moore ◽

Tarik Dickens ◽

Clement Allen

Keyword(s):

Additive Manufacturing ◽

Path Planning ◽

Travelling Salesman Problem ◽

Optimal Path ◽

Planning Problem ◽

Robotic Arms ◽

Optimal Path Planning ◽

Manufacturing Operations ◽

3D Printed ◽

Path Planner

We have designed a path planner for an additive manufacturing (AM) prototype that consists of two robotic arms which collaborate on a single part. Theoretically, with two nozzle equipped arms, a part can be 3D printed twice as fast. Moreover, equipping the second robot with a machining tool enables the completion of secondary operations like hole reaming or surface milling before the printing is finished. With two arms in the part space care must be taken to ensure that the arms collaborate intelligently; in particular, tasks must be planned so that the robots do not collide. This paper discusses the development of a robot path planner to efficiently print segments with two arms, while maintaining a safe distance between them. A solution to the travelling salesman problem, an optimal path planning problem, was used to successfully determine the robots path plans while a simple nozzle-to-nozzle distance calculation was added to represent avoiding robot-to-robot collisions. As a result, in simulation, the average part completion time was reduced by 45% over the single nozzle case. Importantly, the algorithm can theoretically be run on n-robots, so time reduction possibilities are large.

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Autonomous Mobile Robot Navigation in Structured Rough Terrain

Journal of Intelligent Systems with Applications ◽

10.54856/jiswa.201805023 ◽

2018 ◽

pp. 67-74

Author(s):

Azad Asar ◽

Erkan Uslu ◽

Nihal Altuntas ◽

Mehmet Fatih Amasyali ◽

Sirma Yavuz

Keyword(s):

Path Planning ◽

Optimal Path ◽

Path Following ◽

Mobile Robot Navigation ◽

Rough Terrain ◽

Depth Sensor ◽

Navigation Problem ◽

Optimal Path Planning ◽

Localization And Mapping ◽

The Given

Main study areas for robotics research can be given as: mapping, localization, navigation and exploration. Given a robot’s current position, partial map of the environment and a goal position; navigation problem can be defined as optimal path planning and path following. Path planning and path following problem should be handled according to environment being static or dynamic, robot's mobility capabilities, sensors used on the robot and the roughness of the environment. In the study a four wheeled, skid-steering robot with laser range finder and depth sensor is built for Gazebo simulation environment. Also a statically structured labyrinth that consists of 15 degree continuous ramps, 15 degree discontinuous ramps, amorphous holes that robot cannot autonomously escape from if fallen into, walls and discontinuous obstacles that are below the robot laser height. 2D simultaneous localization and mapping, 3D mapping, path planning and path following with respect to the 3D map are implemented on Robot Operating System (ROS). Optimal path planning in rough terrain is accomplished by combining A* heuristic with a function of height difference of the 3D map nodes. Path following is carried out by turning-to and moving-towards actions on each sequential path node pairs. Tests performed on the labyrinth shows that obstacle avoidance, path planning and path following can be carried out successfully with the given implementation.

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Modified Virtual Semi-Circle Approach for a Reactive Collision Avoidance of a Mobile Robot in an Outdoor Environment

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.679.171 ◽

2014 ◽

Vol 679 ◽

pp. 171-175 ◽

Cited By ~ 1

Author(s):

R.N. Farah ◽

N. Irwan ◽

Raja Lailatul Zuraida ◽

Amira Shahirah ◽

Mohd Hanafi Omar

Keyword(s):

Path Planning ◽

Optimal Path ◽

Cost Effective ◽

Outdoor Environment ◽

Unmanned Ground Vehicle ◽

Influence Zone ◽

Two Phase ◽

Ground Vehicle ◽

Optimal Path Planning ◽

Reactive Collision

There are numerous numbers of methods that have been introduced to the Unmanned Ground Vehicle (UGV) to find its optimal path. The purpose of this paper is to navigate a cost effective UGV known as MG-TruckS with optimal path planning in an outdoor environment. A Modified Virtual Semi Circle approach is proposed based on situated-activity paradigm. This approach is divided into two phase to compute a free collision path planning; detection and avoidance phase. Implementation of five ultrasonic range finder sensors with a very small blind zone created on purpose and the formation of three layers of influence zone shows the optimized path planning without making any unnecessary obstacle avoidance being computed.

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