Cleaning Robot Research Articles

Capillary Skimming of Floating Microplastics via a Water-Bridged Ratchet.

Floating microplastics (MPs) have recently become a major concern in marine pollution; however, current filter-based technology is hardly effective for directly removing such MPs from the water surface because of specific mesh size and clogging issues. This paper introduces a new skimming concept for removing floating MPs utilizing capillary force mediated by the elevation of a hydrophilic ratchet at the air-water interface. MPs floating near the ratchet surface are spontaneously forced toward the ratchet with a concave water meniscus, driven by the Cheerios effect. The MPs can then be skimmed and temporarily held by the deforming concave water meniscus as the ratchet rises. Here, it is found that the stability of the water bridge plays a crucial role in skimming success because it provides capillary adhesion between the MP and the ratchet. The proposed capillary skimming method is observed to be effective across nearly all types of floating MPs, ranging in size from 1 to 4 mm, and with densities varying from 0.02 to 0.97 gcm- 3, which is also demonstrated by a prototype of marine robot cleaner.

Mobile-Controlled River Cleaning Robot: A Review

This project focuses more on "Remote Controlled Unmanned River Cleaning Bot". In India water pollution is increasing day by day, Water pollution is a significant environmental issue, with rivers often acting as the primary carriers of waste materials such as plastics, debris, and other pollutants. Current manual cleaning methods are inefficient, costly, and other pollutants. Current manual cleaning methods are inefficient, costly, and unable to access certain areas of the water. This paper presents the development of a mobile-controlled river cleaning robot designed to tackle these challenges. The robot can be remotely operated via a mobile application, allowing for precise control of its navigation and cleaning operations. It is equipped with waste collection mechanisms and sensors to detect and remove debris from the river’s surface. The study covers the design, hardware and software components, and testing of the robot in real-world conditions. Results indicate that the mobile-controlled robot offers an effective, cost-effcient, and environmentally sustainable solution for maintaining cleaner waterways. This innovation has the potential to revolutionize river cleaning processes and significantly reduce water pollution.

A Design Study on Commercial Cleaning Robots Based on Kano–QFD

In the post-pandemic era, public space safety has emerged as a central public concern. As global public health awareness rose, traditional manual cleaning methods were increasingly inadequate for large-scale and high-standard cleaning requirements. Therefore, the design of a commercial cleaning robot that combined cleaning efficiency, environmental performance, and sustainability was essential to meet evolving societal demands. This paper systematically gathered and analyzed commercial cleaning robot functional requirements through a comprehensive investigation. According to the Kano model, functional requirements were categorized by attributes and their importance was quantified. Subsequently, using the QFD model, the design requirements for commercial cleaning robots were determined, and their significance weights were established. This identified the key design requirements. The results of this study indicated that the integration of the Kano and QFD models provided a novel perspective for the design of functional integration in commercial cleaning robots. Furthermore, it provided a practical methodological framework for addressing similar issues in the future.

A Hybrid Attention Mechanism and RepGFPN Method for Detecting Wall Cracks in High-Altitude Cleaning Robots

A Hybrid Attention Mechanism and RepGFPN Method for Detecting Wall Cracks in High-Altitude Cleaning Robots

Research on Path Planning for Industrial Cleaning Robots in Complex Environments: An Enhanced Immunogenetic Algorithm Approach

As industrial automation advances, cleaning robots in complex environments have demonstrated significant value in enhancing efficiency and reducing labor costs. This paper presents a path planning method based on an improved Immune Genetic Algorithm (IGA) for comprehensive coverage path planning in complex industrial settings. Initially, the Boustrophedon Cellular Decomposition (BCD) method is employed to effectively segment the complex scene, identifying key areas for cleaning tasks. Subsequently, the path planning efficiency and adaptability are enhanced through an optimized genetic algorithm that integrates immune memory, Inver-Over operators, and 3-opt operators to refine the traversal sequence between regions. Moreover, this study incorporates the A* algorithm and the Biologically Inspired Neural Network (BINN) algorithm for efficient inter-regional path transitions and precise intra-regional traversal, respectively. A series of simulation experiments validate the superiority of the proposed algorithm in terms of path length, coverage rate, and computational time. The results demonstrate that this method not only effectively addresses the challenges of path planning in complex industrial environments but also significantly improves cleaning efficiency, offering high practical value and potential for broader application.

Path planning of manure-robot cleaners using grid-based reinforcement learning

The use of a robot cleaner for manure removal improves housing conditions for dairy cows in the face of labor shortages. However, current robot cleaners follow programmed fixed routes without considering the dynamic behaviors of cows. This cleaning approach is less efficient and leads to more cow-robot encounters or collisions, thus affecting animal welfare. To address these issues, this paper (1) developed heatmap models for cow locations and defecation behaviors; (2) proposed a dynamic path planning approach for the manure robot cleaner using Grid-based Reinforcement Learning; (3) incorporated cow location information and defecation behavior into the path planning process; (4) compared the performance of the proposed approach with two different cleaning methods: the current fixed programmed cleaning in practice and the ideal path produced by simulated annealing for traveling salesman problem. The simulations mimic the situation in a barn at Dairy Campus of Wageningen Livestock Research located in Leeuwarden (the Netherlands). Obviously, the best performance was achieved when the route was executed without cows present, resulting in no cow-robot collision. However, with cows present, the proposed dynamic path planning strategy achieved a 67.6% reduction in cow-robot encounters while maintaining 85.4% of the cleaning performance compared to the current programmed fixed routes. Compared to the ideal path produced by simulated annealing for traveling salesman problem, the proposed dynamic path planning approach achieved 5% better cleaning performance, at the cost of 25% more cow-robot encounters due to its longer working path. We conclude the proposed grid-based Reinforcement Learning solution for manure robots in barns cleaned most efficient with the least interference with cow traffic.

Abrasion of PV Antireflective Coatings by Robot Cleaning

Abrasion of PV Antireflective Coatings by Robot Cleaning

Design and Self-Calibration Method of a Rope-Driven Cleaning Robot for Complex Glass Curtain Walls

Rope-driven robots are increasingly used to safely and efficiently clean complex glass curtain walls. However, continuous global cleaning is difficult for most robots because of their poor performance in overcoming obstacles and adapting to curved surfaces, and an inconvenient winch calibration on complex surfaces further burdens such work. This paper presents a 3-DOF rope-driven robot and a winch self-calibration method for efficient cleaning. The robot, by integrating a 5-rope parallel configuration, a self-adaptive cleaning body, and a self-compensating driving winch, is designed to perform continuous, compliant, and accurate spatial motion on curved walls with obstacles. By deducing the kinematic model, the constraint relationship related to orderly arranged winch positions, maneuverable body positions, and accessible rope lengths is established during the robot tracking 3D trajectory. Combining the established relationship, a series of regulations are formulated for easily acquiring body positions and rope lengths, and then a self-calibration method is proposed by accurately calculating winch positions without using professional instruments. Experimental results show that the robot can perform global and precise movement on complex glass surfaces. Applying the proposed method, the maximum winch calibration error is 6.6 mm, and the maximum body tracking error is controlled within 9.6 mm.

Design & Fabrication of Water Optimized - Solar Panel Cleaning Robot

Abstract: Maintaining a power capacity of solar cell is the main thing for exercising solar power system. Most common problems in solar power system are dust, beach, creature’s pollen and crops burning. These challenges have a huge impact on the power generation capacity of solar panel. The thing of the robot's conception design is to make a machine that's easy to install, adaptable in terms of configuration, and requires lower labourers and functional charges. The robot is equipped with helical comber skirmishes which are driven by dc motor so that the robot is enforced with a water sprinkle in order to clean the panels far and wide it moves through. In this design, a system contains a length dimension unit and bedded control schemes in order to drive a movement directly and to localize the positions of the robot.

Smart Robot Cleaner Using Internet of Things

The most dreaded chore is cleaning the house where it is at the top of the list for many people. Cleaning the house is time consuming and must be carried out continuously. This study aims to design an autonomous robotic cleaner for a self-driving robot that automatically cleans the floor. The Smart Robot Cleaner is proposed and established using the Internet of Things (IoT). The robot is equipped with microfiber cleaning, a water tank, a water pump, ultrasonic sensors, a DC motor, a hose tube, and a wheel. The Arduino Uno is used as the main component and is connected with an ultrasonic sensor to detect any object and obstacles. To allow Internet of Things functions in this robot, the Bluetooth module is used as a command from the smartphone to control the movement. The experimental results showed that the performance of the proposed smart robot cleaner is able to clean various dirt, such as water, milk, and sauce. The robot can be manually and automatically controlled via smartphone.

Autonomous robot vacuum system composed of a cleaner robot and a dust storage robot

In this paper, we address an autonomous robot vacuum system, composed of two robots. Conventional robot vacuum has a small dust bin, and its suction power is low. This low cleaning power has been considered as a defect of a conventional robot vacuum. If we use a large robot vacuum with high cleaning power, then we cannot clear various narrow environments, such as narrow space under a sofa. To resolve this problem, we address an autonomous robot vacuum system composed of a small Cleaner Robot (CR) and a large dust Storage Robot (SR). The CR and the SR are connected using a hose, thus they must maneuver as a pair. The role of the small CR is to clean various environments, such as narrow space under a sofa. The CR is small, thus it cannot contain a large motor for increasing its cleaning power. The dust sucked by the CR is transmitted to the SR through the hose. The SR is large, hence it can have a large motor for increasing its cleaning power compared to a conventional robot vacuum. To the best of our knowledge, our paper is novel in addressing an autonomous robot vacuum system composed of a CR and a SR. Our paper is unique in addressing the path plan of these two connected robots, so that the entire open workspace can be cleaned by the CR as fast as possible. Under MATLAB simulations, we demonstrate the effectiveness of path planning for our autonomous robot vacuum system. We show that the proposed tethered robots improve the cleaning efficiency, compared to the case where a single large robot vacuum is applied.

Floor Cleaning Robot using Android App

The contemporary household landscape is witnessing a paradigm shift towards enhanced intelligence and automation. The integration of home automation systems not only provides increased convenience but also affords individuals more time for other pursuits. This project endeavors to conceptualize and actualize a Vacuum Robot that operates autonomously and manually through a designated mobile application. The Vacuum Cleaner Robot, utilizing components such as Arduino Mega, Arduino Shield, LDR Sensor, Real-Time Clock, Motor Shield L293D, Ultrasonic Sensor, and IR Sensor, aims to streamline the cleaning process, replacing manual vacuuming with an efficient automated solution. The primary objective of this initiative is to successfully design and implement a prototype Vacuum Robot that adheres to user-friendly criteria outlined in the aforementioned context.

Solar Panel Cleaning Robot

In this project, various studies revolving around how dirt and dust affect the performance of solar panels depending upon different regions, as different areas have different soil compositions and how they are different from one another. A new way of approach to the domestic solar panel cleaning system, researchers have proposed many ways to improve and classify the object and present it in an image in the past. However, there have few projects related to domestic cleaning of solar panels. Due to the inconsistencies in cleaning especially in region where rain is not the most convenient option for cleaning. On continuous using of solar panels, a layer of accumulated dust particles is settled on the surface of solar panels or PV panels which affect the result of decreasing in efficiency by 50 %. By cleaning on regular intervals it decreases this soil loss. Various data have been collected which shows the importance of domestic solar panel cleaning for future generation.

The Design and Analysis of a Tunnel Retro-Reflective Ring Climbing and Cleaning Robot

The Design and Analysis of a Tunnel Retro-Reflective Ring Climbing and Cleaning Robot

Machine Learning-Based Control of Autonomous Vehicles for Solar Panel Cleaning Systems in Agricultural Solar Farms

This paper presents a machine learning (ML)-based approach for the intelligent control of Autonomous Vehicles (AVs) utilized in solar panel cleaning systems, aiming to mitigate challenges arising from uncertainties, disturbances, and dynamic environments. Solar panels, predominantly situated in dedicated lands for solar energy production (e.g., agricultural solar farms), are susceptible to dust and debris accumulation, leading to diminished energy absorption. Instead of labor-intensive manual cleaning, robotic cleaners offer a viable solution. AVs equipped to transport and precisely position these cleaning robots are indispensable for the efficient navigation among solar panel arrays. However, environmental obstacles (e.g., rough terrain), variations in solar panel installation (e.g., height disparities, different angles), and uncertainties (e.g., AV and environmental modeling) may degrade the performance of traditional controllers. In this study, a biologically inspired method based on Brain Emotional Learning (BEL) is developed to tackle the aforementioned challenges. The developed controller is implemented numerically using MATLAB-SIMULINK. The paper concludes with a comparative analysis of the AVs’ performance using both PID and developed controllers across various scenarios, highlighting the efficacy and advantages of the intelligent control approach for AVs deployed in solar panel cleaning systems within agricultural solar farms. Simulation results demonstrate the superior performance of the ML-based controller, showcasing significant improvements over the PID controller.

AI Powered Cleaning Robot

AI Powered Cleaning Robot

Design and Development of River Cleaning Robot Using Iot Technology

The issue of waterlogging due to plastic, thermocole and metal is prompting bother development, and it favors ailments like intestinal sickness, typhoid and so on. Cleaning the wastes by utilizing manual procedures would be insufficient as it regularly covers immense territory of works and endeavors with plausibility to getting influenced by different sicknesses from the irresistible microorganisms present in the sewage while cleaning manually. This study features a proposed plan of garbage gathering system viable and effective for tidying up waste from rivers, channels and lakes. The trash gathering system is explicitly coordinated to application for getting up a wide assortment of debris, including gliding litter, trash, logs, disposed tires and others. The integrated system incorporates the usage of IoT technology that has the ability to monitor and control the entire process. From the interest and need of cleaning contaminations in the conduits territory, the vessel has been created to suit the prerequisite of working at places other than seaward zone, giving more decisions for the utilization of cleaning garbage and waste from the water environment. Keywords— river cleaning robot, design & simulation, IoT

Automatic Vacuum Cleaner Robot

Automatic Vacuum Cleaner Robot

Research on Autonomous Navigation and Intelligent Recognition Technology of Ship Hull Cleaning Robots Based on Deep Learning

Research on Autonomous Navigation and Intelligent Recognition Technology of Ship Hull Cleaning Robots Based on Deep Learning

Smart Vacuum Cleaning Robot

In today's fast-paced world, the demand for efficient and convenient household technologies continues to surge. Among these, smart vacuum cleaning robots have emerged as indispensable tools, promising automated cleaning solutions that integrate seamlessly into modern lifestyles. This abstract presents a comprehensive overview of a cutting-edge smart vacuum cleaning robot embedded system, featuring five key components for enhanced functionality. The system is anchored by an Arduino Nano-based model, leveraging the versatility and reliability of Arduino technology to orchestrate the robot's operations. Through a Bluetooth-operated interface facilitated by a dedicated mobile application, users can effortlessly control the robot's movements and cleaning schedules, offering unparalleled convenience and flexibility. Equipped with a dry vacuum cleaning system optimized for dust collection, the robot ensures thorough cleaning performance while minimizing maintenance hassles. Additionally, an ultrasonic sensor serves as a robust obstacle detector, enabling the robot to navigate intelligently and avoid collisions with furniture and other obstructions. Crucially, the entire system operates on a battery-powered module, granting the freedom to traverse various spaces without constraints imposed by traditional power sources. By synergizing these components, the proposed smart vacuum cleaning robot embedded system epitomizes the convergence of innovation and practicality, poised to revolutionize the landscape of home cleaning automation.