PRE2017 3 Groep3

Subject

The subject for this project was chosen to be: Motion planning algorithm for window cleaning robots.

Objectives

• Literature study of current window cleaning robots and USE aspects regarding window cleaning robots.
• To develop an efficient cleaning algorithm that cleans a window which satisfies certain requirements on cleaning speed, water consumption, energy consumption.

Final Products

The final products of this project is a NetLogo model of a window clean robot on a dirty window surface. Within this model, it will be possible to perform the process of cleaning the window with regard to several different motion planning algorithms that will be designed during this project. The data output from this model can then be analyzed and compared to find a better and the best performing algorithm with respect to the current motion planning of these robots.

All information about the project found on the WIKI page is also orderly put together in the form of a technological report about the chosen subject.

The NetLogo model:
NetLogo model

Report group 3-Motion planning algorithm for window-cleaning robots:
0LAUK0 report group 3: Motion planning

Introduction

Every year there are major innovations in the field of technology. Self-driving cars, reusable rockets and even face-recognition abilities of current smart-phones are some examples. Not all innovations, however, get the same amount of attention and some are thus less widely known. This report focuses on the improvement of a small and less impact full technological piece of equipment, namely the window cleaning robot. Window cleaning robots are currently built for two main application domains, domestic use and professional use on big skyscrapers or flats. The advancements in the capabilities of these window cleaning robots are still in the early stages. Nevertheless, there is already a range of window cleaning robots available on the market, differing in size and performance. However, the existing window cleaning robots for domestic use have all a major shortcoming in common: their movement is based on a simple, inefficient motion planning. This is mainly due to the thought of minimal gain and the aim for simplicity. Therefore, an optimized motion planning algorithm is developed in this project. This optimized algorithm will be applicable to the smaller sized window cleaning robots that are used for domestic applications. The design question is:

How should the main, currently used a motion-planning algorithm for small sized window cleaning robots for domestic use be improved such that it is more efficient in terms of cleaning speed, energy consumption, and water consumption?

The answer to this question will be relevant for the users, window cleaning companies, since they can buy a set of window cleaning robots operating on this algorithm to improve their services and increase their revenue as an enterprise. Besides that, the developed algorithm will help the customers through better scheduling and faster clean ups and help society through advancement of planning-algorithms which may spark further improvements on the algorithms of motion planning robots.

The main scenario for which the motion planning is designed is a small window cleaning company that has multiple cleaning robots in its possession, with one employee who can move the cleaning robots from one window to another, allowing him to clean multiple windows simultaneously, thereby reducing the time it takes to clean all the windows in the building and reducing labor cost.

This report consists of six chapters, starting with a literature study on the capabilities of current window cleaning robots and their motion planning algorithms. Followed by a systematic design process, including approach, user requirements, design choices, concepts, assumptions, robot specifications and a simulation model. In this model the performance of two innovative algorithms will be tested and compared to the current approach listed in the literature study. The results from the model will subsequently be thoroughly evaluated. At the end, a well-funded conclusion will be given.

Users

The users, in this case, are window washing companies that can use window cleaning robots to improve their services. The considered scenario is that these companies are hired by private individuals to clean the windows of their houses. The faster and cheaper these companies can accomplish this, the more profit they can make. A major help for this purpose would be to develop an algorithm that determines how to clean the windows of a house in the most efficient way possible when the dirt distribution on the windows is taken into account.

In order to develop the model, requirements, preferences, and constraints should be made explicit. If one considers the view of the users, the window washing companies, the following requirements, preferences, and constraints could be distinguished:

Requirements

• The robot should at least inspect or clean every window one time, regardless of the dirtiness of the window. In other words, windows that are not dirty should be inspected at least once. This is a very reasonable requirement, because people who hire a window washing company expect that they will do every window.
• The window cleaning robot is not allowed to leave stripes due to the dripping of water or incomplete horizontal movements.
• For window washing companies, speed in terms of surface area cleaned per unit of time is of major importance. The higher the speed with which the windows can be cleaned, the more profit that can be made. The goal is to reach a speed of 71 m^2 / hr, which is the mean of three popular commercially available window cleaning robots that are considered (see Appendix \ref{app: table robots appendix}). This seems an acceptable requirement for the model.
• The water consumption is another important aspect, since this has an impact on the speed of the cleaning process and also has a minor impact on the total cost of the cleaning job. All current window cleaning robots of the here considered size do not have a water supply or tank, but use detergent instead. The innovative part of the model is therefore that a water supply is included. This is similar to real window washers, because they also do not use detergent solely. The requirement for the water consumption is based on a bigger window cleaning robot (GEKKO Facade Robot \cite{gekko facade robot}) which has a water consumption of approximately 1 L / min. Because this bigger robot has a size of around 4 times the size of the considered cleaning robots, a requirement of 0.25 L / min seems suitable.
• Energy consumption is the last relevant aspect, since this has an impact on the total cost of the cleaning job. The requirement for the energy consumption is also determined by averaging over the considered window cleaning robots: 73.5 W (see Appendix \ref{app: table robots appendix}).

Preferences

• The window should be made as clean as possible.
• Speed in terms of surface area cleaned per unit should be as high as possible.
• Water consumption should be as low as possible, since it is better for the environment than conventional detergents.
• Energy consumption should be as low as possible.

Constraints

• The robot should be able to clean windows with a dimensions between 0.5 x 0.5 m and 4.0 x 4.0 m. In this range the most common windows will be covered.

State-of-the-art

The list below gives an overview of the summaries of the articles which have been studied. The articles are divided into subcategories.

Window cleaning robot design

• A Gecko Inspired Fluid Driven Climbing Robot
• Development of a High Efficiency and High Reliable Glass Cleaning Robot with a Dirt Detect Sensor
• SkyScraper-I: Tethered Whole Windows Cleaning Robot
• WINDORO : The World’s First Commercialized Window Cleaning Robot for Domestic Use
• SMART WINDORO V1.0: Smart Window Cleaning Robot
• A Small Window-Cleaning Robot for Domestic Use
• Window Cleaning Robot ASME Design Competition
• Sensor Based Motion Planning and Estimation of Highrise Building Façade Maintenance
• Design and stability analysis of a novel wall-climbing robotic platform (ROPE RIDE)
• Climbing cleaning robot for vertical surfaces
• Implementation of glass-curtain-wall cleaning robot driven by double flexible rope
• Analytical modelling of suction cups used for window-cleaning robots

Issues encountered while performing cleaning task

• Inferring the Effects of Wiping Motions based on Haptic Perception
• A wall climbing robot for inspection use
• Experimental comparison of drag-wiper and roller-wiper glass-cleaning robots

Movement over façade

• Design and Kinematic Analysis of Tethered Guiding Vehicle (TGV) for façade window cleaning
• A Path Motion Planning For Humanoid Climbing Robot
• A survey of climbing robots: Locomotion and adhesion
• Motion planning algorithms for autonomous robots in static and dynamic environments
• A survey on coverage path planning for robotics

Movement over window

• Calculation of Optimal Magnetic Force for Automatic Control Magnetic Force of the Window Cleaning Robot
• Window cleaning system with water circulation for building façade maintenance robot and its efficiency analysis
• Dense topological maps and partial pose estimation for visual control of an autonomous cleaning robot
• Design and stability analysis of a novel wall-climbing robotic platform (ROPE RIDE)

Acceptance of robots and engagement with robots

• From a Robotic Vacuum Cleaner to a Robot Companion: Acceptance and Engagement in Domestic Environments

Approach

Prior to the development of the model, a literature study on currently available window cleaning robots is performed (see Chapter \ref{sec:state of the art}). This literature study was actually the motivation to design an efficient motion planning algorithm for window cleaning robots.

The design process of the motion planning algorithm is divided into the following steps:

1. Analysis of the user and user requirements, preferences and constraints
2. Conceptualization
3. Choosing the best solution
4. Modeling the motion planning algorithm by means of NetLogo
5. Refine the motion planning algorithm
6. Evaluation of the obtained results

After each step the solutions or results are fed back to the requirements, preferences and constraints defined in step 1. This makes sure that the user stays central during the whole design process and undesirable results are prohibited.

Planning, milestones & deliverables

Week	Goal	Milestones	Deliverables
1	Finish work plan Finish literature study and SotA	Finished literature study and SotA	Work plan Summaries of articles
2	Confirm definitive subject and project goal Adapt the project planning	Clear and measurable project goal	Project planning
3	Divide the possible approaches to window-cleaning algorithms, and research them Start the basis of the algorithm/ simulation Precisely anylise users and user needs Create a list of precise measurables and ways to achieve these numbers Research potential simulation programs and get handy with the coding skills needed	Clear vision of the project to all members and a definitive goal and approach to the problem	Sheet of potential algorithms with their pro and cons Definitive program in which model simulations will be done
4	Check whether algorithm satisfies the requirements, preferences, and constraints of the group, adapt the algorithm accordingly. Choose a definitive algorithm approach and start the programming of the simulation	Definitive algorithm which can be simulated and results in the measurables wanted. (close to completion simulation)	Finished or close to finished programmed model simulation
5	Analysis of the simulation; expected results, satisfying results? Further improvements to the algorithm. Start writing report	Finished and analyzed model.	Measurables compared to expectations.
6	Start report work; divide chapters into; introduction, theory, algorithm, simulation, results, conclusion, future improvements and appendices.	Finished report	Correct report and simulation
7	Buffer time - finish report.

Task division

Week	What?	Who?
1	Finish work plan Finish literature study and SotA (Everybody searches 5 articles, reads them and summarizes them)	Everybody together Everybody
2	Finish analysis of the user and user needs Edit project planning and update wiki with references Finish SotA	Lars, Kylian Ibrahim, Jorick Ezra
3	Specify the model design Program a basic window in Netlogo Research implementation of water usage Research implementation of energy usage Coaching questions + update planning and division of tasks on wiki	Kylian Lars Ibrahim Ezra Jorick
4	Start modeling the motion planning of the robot into Netlogo Research turning paths and times for robot Write report about the first half of the project Specifically describe the robots attributes and functions	Jorick, Kylian Ezra Lars, Ibrahim Lars, Ibrahim
5	Further programme the netlogo behaviour Programme a better dirt distribution Write about algortihm Update state of the art Mathematics and explanations behind turning behaviour in report Fix contradicting statements in report How to incorperate weight of the robot into model Summeries the possible factors in which time savings can be had	Lars, Kylian Kylian Lars Ibrahim Ezra Jorick Jorick, Ibrahim Jorick, Ibrahim
6	Finish model Compare final results from model with controll values Finish report	Lars, Kylian Jorick, Ibrahim Everybody
7	Finish report	Group work

Work on the model

Setup of the model

For the setup of the motion planning algorithm (the concept, assumptions and simplification, etc.), we would like to refer to the report, see the section below.

Current state of the model
The following things are already modeled:

• Window is programmed on which a random dirt distribution appears (also with clusters dirt).
• The robot is modeled in such a way that it represents reality.
• The robot can move
• The robot is able to clean the whole window by doing a standard zigzag motion.
• Rotation times that are analytically determined (video of a possible movement pattern + movements) are implemented in the model.

The model looks currently as follows:

The following things should still be implemented:

• Making the robot able to clean windows with heights that are not a multiple of the robot dimensions.
• Implementing that short zigzag motions should be performed when the robot moves over persistent spots of dirt.

Work on the report

The current state of the report can be seen by using the following link: [1].report

Coaching Questions

Coaching Questions Group 3

The links below refer to pages with the coaching questions of each week.

• Week 1: Coaching Questions
• Week 2: Coaching Questions
• Week 3: Coaching Questions
• Week 4: Coaching Questions
• Week 5: Coaching Questions
• Week 6: Coaching Questions
• Week 7: Coaching Questions

References

[1] Akinfiev,T. Armada,M. & Nabulshi,S. (2009). Climbing cleaning robot for vertical surfaces. Industrial Robot: An International Journal, Vol. 36 Issue: 4 pp.352-357.
[2] Barbut,O. (2008). Window Cleaning Robot ASME Design Competition. Department of Mechanical Engineering Toronto.
[3] Choi,Y. & Jung,K. (2011 November 26). WINDORO: The World's First Commercialized Window Cleaning Robot for Domestic Use. Pohang Institute of Intelligent Robotics Korea.
[4]Choi,Y-H. Lee,J-Y. Lee,J-D. & Lee,K-E. (2012 November 29).SMART WINDORO V1.0: Smart Window Cleaning Robot. Korea Institute of Robot & Convergence.
[5] Chu,B. Jung,K. Han,C. & Hong,D.(2010 August). A Survey of Climbing Robots: Locomotion and Adhesion. Department of Mechanical Engineering South Korea.
[6] Galceran,E. & Carreras,M.(2013 August 5). A survey on coverage path planning for robotics. University of Girona Spain.
[7] Gandhinathan, R. & Ambigai, R. (2016). Design and Kinematic Analysis of Tethered Guiding Vehicle (TGV) for façade window cleaning. Department of Mechanical Engineering India.
[8] Gerstmayr-Hillen,L et al. (2013 January 17). Dense topological maps and partial pose estimation for visual control of autonomous cleaning robot. Computer Engineering Group , Faculty of Technology Germany.
[9] Imoaka,N. Roh,S. Yusuke,N. & Hirose,S. (2010 October 22). SkyScraper-I: Tethered Whole Windows Cleaning Robot. Design of Moving Mechanisms and Preliminary Experiments Taiwan.
[10] Jiang,J. Zhang,Y. & Zhang,S. (2014).Implementation of glass-curtain-wall cleaning robot driven by double flexible rope. Industrial Robot: an International Journal, Vol.41 Issue: 5 pp.429-438.
[11] Katsuki,Y. Ikeda,T. & Yamamoto,M. (2011 September 30). Development of a High Efficiency and High reliable Glass Cleaning Robot with a Dirt Detect Sensor.
[12] Lee,J. Choi,Y. & Lee,J. (2013 November 2). Calculation of Optimal Magnetic Force for Automatic Control Magnetic Force of the Window Cleaning Robot. Korea Institute of Robot and Convergence Korea.
[13] Lee,S. Kang,M. & Han,C. (2012 December). Sensor Based Motion Planning and Estimation of High-rise Building Façade Maintenance Robot. Department of Mechatronics Engineering South Korea.
[14] Leidner,D. & Beetz,M. (2016 November 17). Inferring the Effects of Wiping Motions based on Haptic Perception.
[15] Lui,J. Tanaka,K. Bao,L M. & Yamaura,I.(2005 October 3).Analytic modeling of suction cups used for window-cleaning robots. Department of Functional Machinery and Mechanics Japan.
[16] Liu,J. Jiang,H. Li,Z. & Hu,H. (2009). A Small Window-Cleaning Robot for Domestic Use. Jiangnan University China.
[17] Liu, J. et al. (2011 May 9). A Gecko Inspired Fluid Driven Climbing Robot. Institute Of Mechatronic Control Engineering Zhejiang University.
[18] Lupetti,M L. Rosa,S. & Ermacora,G. From a Robotic Vacuum Cleaner to a Robot Companion: Acceptance and Engagement in Domestic Environments.
[19] Moon,S M. Shin,C Y. Huh,J. Won,K. & Hong,D. (2015 January). Window Cleaning System with Water Circulation for Building Façade Maintenance Robot and Its Efficiency Analysis. School of Mechanical Engineering South Korea.
[20] Nguyen,D. & Shimada,A. (2013). A Path Motion Planning For Humanoid Climbing Robot. Shibuara Institute of Technology Japan.
[21] Nishi,A. A wall climbing robot for inspection use. Miyazaki University Japan.
[22] Palleja,T. Transanchez,M. Teixido,M. & Palacin,J. (2009 August 11). Modeling floor-cleaning coverage performance of some domestic mobile robots in a reduced scenario. Department of Computer Science Spain.
[23] Seo,K. Cho,S. Kim,T. Kim,H S. & Kim, J. (2013 August 15). Design and stability analysis of a novel wall-climbing robotic platform (ROPE RIDE). Mechanism and Machine Theory pp.189-208.
[24] Zanele,G N M. (2011 June). Motion Planning Algorithms for Autonomous Robots in Static and Dynamic Environments. University of Johannesburg.
[25] Zhou,Q. & Li,X. (2016). Experimental comparison of drag-wiper and roller-wiper glass-cleaning robots. Industrial Robot: An International Journal, Vol.43 Issue:4, pp409-420.