RV College of Engineering®
(Autonomous Institution Affiliated to VTU, Belagavi)
SMART WINDOW CLEANER
Experiential Learning Report
Submitted by
STUDENT NAME- USN
ADITYA RAJ-1RV21EE004
GOURAV KUMAR-1RV21EE024
B ADITYA-1RV21EE019
NISHAANTH S-1RV21EE041
Electrical and Electronics engineering
Submitted to
FACULTY NAME
Prof. SAILAJA Y
Dr. R. MAHESH
Prof. VANISHREE K
Dr. ROOPA T S
Prof. CHETHANA G
Contents:
1. Introduction.
2. Literature Review.
3. Objectives.
4. Problem Statement.
5. Methodology.
6. Block Diagram/Algorithm/Flowchart
7. Implementation and Result.
8. Conclusion and Future Work.
9. References
ABSTRACT
The idea of having a compact and autonomous office or house window
cleaning robot is quite simple and very attractive. This small window
climbing robot with pneumatic suction cups should be able to move
autonomously along an outside surface of high-rise building office window
with a relatively large area and meantime clean and wash it. Being manually
attached to the outside surface of the room window the robot will execute
and accomplish the task of window cleaning automatically in a predefined
pattern. The sensory system will help to navigate the robot. It is noted that
window cleaning robots are commercially available but pricey (in the range
of USD 5000 or more). The designed robot is lightweight, small size and
cheap because it is driven only by one rotary actuator and system of
properly arranged conventional belts and pulleys. It uses the suction cups to
stick to the window panel and set of optical sensors to detect the window
frame. The micro-controller is programmed to move the robot in a specific
pattern depending on the sensory data. There are no similar reasonably
priced rival products available in the market yet.
INTRODUCTION
Normally cleaning of wide windows on tall and multi-story buildings is
quite tedious and very dangerous procedure. It can be done outside either
using hoisting machines with manual cleaning or very rare by sophisticated,
complex, large, heavy and very expensive automatic cleaning machines
operated manually from the ground floor. These large machines, besides,
have-to carry a bunch of umbilical pneumatic and electrical cables while
cleaning the windows. As a result, they are not popular in housekeeping
operations. Therefore, the use of autonomous window climbing and
cleaning robots attracted the attention of many designers.
In recent times, the requirement for a clean, safe, healthy, and eco-friendly
life has driven the advancement of more robotic innovations for cleaning.
The periodic cleaning in unreachable locations of the building facade, solar
panels is a challenging issue worldwide, particularly in Asian nations. The
human operators generally utilize suspended gondola or wire ropes to
reach these locations, which is probably more unsafe, dangerous, and quite
time-consuming work. Research interest in developing various autonomous
wall-climbing robots capable of maneuvering on vertical or inclined wall
surfaces could replace human efforts in cleaning.
The wall-climbing robot locomotion techniques are mostly similar-to the
ground mobile robots, such as: wheel, arm/leg, chain/track, translation/
sliding frames, roof supported wires/cables, built-in guide rails, and multilocomotion. A robot development using the climbing method like multi
suction cups has also been studied to clean photovoltaic (PV) solar panels.
The automatic robotic cleaning concept can be more beneficial for dust
cleaning from the unreachable location of PV solar panels to enhance
efficiency for PV power generation.
Dynamic model of the wall-climbing robot for vertical wall locomotion
requires modeling of adhesion force generated by adhesion mechanism,
wall surface inclination, gravity force and the coefficient of friction between
robot and wall surface. These factors greatly influence the motion control
characteristics of the wall-climbing robot particularly for glass facade
cleaning. The appropriate dynamic modeling for efficient coverage path
planning of the GFCR is essential to know the climbing action of the robot in
a given desired path for cleaning.
Materials and Methods
 Working concept
Glass facade cleaning robot can be a more effective solution to avoid manual cleaning in a
very high-risk work environment of multi-story buildings. The proposed design concept of the
glass facade cleaning robot (GFCR) consists of two components. The main component is the
GFCR with roller brush cleaning and its various mechanisms, and the other component is a
three-degrees of freedom (DOF) rooftop-assisted device. The purpose of having the roof
assisted device is to safeguard the GFCR in case of any pneumatic vacuum supply and
locomotion failures and also to help the GFCR to position from one glass facade to others
very easily. We can make the connection between the GFCR and rooftop assisted device
through a wire-rope and pulley arrangements for positioning of the robot from one facade to
another. Once placed on a glass facade, it is ready for the cleaning operation by its own
locomotion and adhesion techniques.
 Robot design and Mechanism
The robot is driven by two pairs of front and rear track wheels at each side of the timing-belt
mechanisms. The assembly of the GFCR comprises four pairs of front and rear track wheels
(left and right side), two-timing belt mechanisms (left and right side), and a base platform
comprises of a roller brush and steering mechanisms. The tail end of a roller cleaning brush
arm is connected to the robot base plate by a passive revolution joint. The driving motors with
gear mechanisms are connected with the respective mechanisms for various desired robot
motions.
 Steering mechanism
The steering mechanism presented in the GFCR has a fixed part attached to the robot base
plate and other part is movable with the help of a pair of the lead screw and a combination of
ring-gear and pinion mechanisms. Epicyclic gear train with lead screw mechanism delivers to
the desired steering action along with the active and passive suction attachment of the robot
while climbing. A sharp turning of the GFCR is done by activation of vacuum inside the round
suction cups of the steering mechanism to stick with the glass wall surface. The robot body is
free to turn about the steering mechanism by controlling the connected motors with epicyclic
gear train or opposite motion of the timing-belts. A rotary joint mechanism is provided with the
steering mechanism to avoid tangling of pneumatic tubes connecting the multi-round suction
cups.
 Timing-belt mechanism
The inside view of timing-belt mechanism is used to provide simultaneous locomotion and
adhesion during climbing of the robot. It is further divided into four parts viz., adhesion,
motorized track-wheels, rotary joint and guide-rail mechanisms. The adhesion mechanism
has a spring-loaded piston unit attached with a suction cup to make ON and OFF when it is
engaged and disengaged from the wall surface, respectively. The suction cup ON/OFF
operation is performed by the guide-rail mechanism which guides all the adhesion me
mechanisms and controls the suction while the motorized track-wheel provides continuous
motion. The creation of active vacuum is due to a cam profile at the bottom surface of the
guide-rail mechanism. The unyielding of vacuum is due to the groove at the remaining curved
and upper surface of the guide-rail mechanism. The provision for active suction arrangement
has also been incorporated in the timing-belt mechanism using flexible polyurethane (PU)
tubing and rotary joint mechanism. The rotary mechanism is designed to connect all the oval
suction cups of the timing-belt mechanism by flexible PU tubes.
Mathematical modeling
The schematic representation of GFCR is depicted for mathematical
formulation. Optimal adhesion force analysis has already been done in the
previous work for robot locomotion without any mode of failure, such as
sliding and toppling while climbing. This section presents the kinematic and
dynamic modeling of the proposed GFCR.
 Kinematic model
An inertial frame is attached to the inclined/vertical glass wall surface. Frame {0}
indicates the GFCR base frame, and {C} is placed at the CG of the GFCR. A non-holonomic
GFCR platform motion is represented in terms of generalized coordinate vector q = [xc yc
θ θrt θlt ]T . The position of the robot CG is defined by (xc, yc) and θ(t) is the robot
orientation with respect to the inertial frame {A}. The angular motions of the right and
left side timing-belts are denoted by θrt and θlt , respectively. The points Po and P1
indicate the point of intersection between the axis of symmetry of the robot body and
the axis of the front and rear driving wheels, respectively. The point Pc indicates the
robot CG. d is the distance from Po to Pc, b is the distance between the robot axis of
symmetry and axis of the either driving timing-belt, r is the radius of each track wheel, h
is the height of the robot CG measured from the inclined/vertical glass wall surface, and
φ is the wall inclination angle.
The non-holonomic motion constraints of the GFCR can be expressed in the matrix form
as:
The position motion constraint is obtained by integrating the velocity constraint, and it
leads to a holonomic constraint relation: θ = c( ̇θrt - θit ), where c is defined as:(r/2b),
cθ=cos(θ), sθ=sin(θ) .
Further, a null space matrix S(q) ∈ R5 × 2 of the robot motion constraint matrix B(q) ∈ R3
× 5 is expresses the following relation: B(q)*S(q)=0 .
Kinematic model of the glass façade cleaning robot is then given by: q = S(q)z(t),
where newly introduced variable describes the angular velocities of right and left timing
belts,
 Dynamic modeling
In this section, the Lagrange’s formulation is employed to derive the
dynamic equations of the glass facade cleaning robot. The Lagrange
formulation for constraint system is expressed as:
In the above equation, j = m is the number of constraints, i = n is the
number of generalized coordinates and bj i elements of the kinematic
constraints. Further, the dynamic system can be written in the following
simplified form.
From the quasi-static relations, the required minimum adhesion force (Fa )
is expressed as follows to avoid the robot locomotion failures such as sliding
and toppling from the inclined/vertical wall surface,
Chemicals used as Cleaner
A cleaning product is a blend of specialty materials used to remove soils and
stains from a surface and to restore the surface to its original
condition. Cleaning products are also used to help remove unwanted
microbial contaminants from a surface.
Cleaning plays an essential role in our daily lives by providing important
public health benefits to consumers beyond the obvious aesthetic
benefits. Keeping surfaces clean and free of soil not only helps reduce the
opportunities for spreading of germs but helps extend the life of our
personal possessions.
This site was created by industry experts, with a combined experience of
over 150 years of cleaning product knowledge regarding the following:

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
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

Formulation
Ingredient chemistry
Product testing
Scientific development
Cleaning Methods
Safety and Procedure
Glass cleaner is one of the sub-classes of household cleaners.
Manufacturers use a variety of chemical ingredients to compose their own
glass cleaner’s formula, distinguished by the cleaning strength, mild,
wetting agent, and performance additives.
Chemicals used in glass cleaner
 Surfactant
Chemicals that molecularly surround contaminants and break their hold
or bond on glass surfaces.
1. Anionic surfactant
2. Non-ionic Surfactant
3. Amphoteric Surfactant
4. Alkyl Polyglucosides
5. Special products
6. Surfactant systems
7. Performance additives
 Solvents
Chemicals that molecularly attack and destroy contaminants. Solvents
create chemical reactions that dissolve dirt, fat, grease, or mineral
compounds and make them disappear from dirty surfaces. These
properties lead to effective window cleaning.
 Other Additives
1. Dye: a coloring agent
2. Fragrances: odor-enhancing agents
3. Preservatives

Typical formula for glass cleaner
Trajectory tracking simulation
Trajectory tracking simulation using the derived dynamic model of GFCR provides the
relevant information for robot path planning and motor sizing, such as torque and power
required. A hybrid PID-PSO algorithm and its characteristics have been evaluated in
detail for trajectory tracking simulation of the GFCR. For energy optimal motion
planning, it is necessary to obtain the energy consumed during the robot motion in a
particular path by evaluating the actuator’s torque as well as velocity from the trajectory
tracking simulation.
Path planning simulation
The GFCR is to be simulated for various planned paths such as spiral line sweep, vertical
line sweep, horizontal line sweep, spatial cell diffusion, and their combination, etc. For
efficient coverage, the repetition of motions along with energy consumption has to be
minimized. Therefore, out of these six path options, four robot paths such as horizontal
line sweep (HLS), vertical line sweep (VLS), spiral line sweep (SLS), and special cell
diffusion (SCD) motion with minimum repetition have been selected for the evaluation
of efficient path planning and simulation. Each of these paths has two options viz.
option-1 and 2 for the robot in and out motion for cleaning within a section of the glass
façade. The black arrow (option-1) shows downward cleaning operation on the glass
façade while the red arrow (option-2) shows the upward cleaning operation. Therefore,
there are a total of eight cases for the evaluation of efficient coverage path planning
simulation.
Path planning strategies for a vertical glass
window cleaning by the robot:
 The developed control algorithm using hybrid PID-PSO approach for
energy-efficient coverage of the GFCR for cleaning the glass facade is
represented in the above flowchart.
 Let us consider a single section of glass facade, i.e., surface area of a
glass facade in which the robot moves and cleans for the given
workspace. For efficient coverage, the GFCR has to be consumed less
energy as well as less overlapping area.
 The path planning algorithm investigates energy consumption and
other maneuverability issues for various path planning.
Robot prototype for experiments
 Robot hardware
The robot hardware in is assembled by four main components viz., timingbelt mechanisms (left and right side), rotary mechanisms (left and right
side), electronic control box, and a base platform comprising of a roller
brush and steering mechanisms. Some of the robot hardware like guide-rail,
track wheel etc. are manufactured in CNC technique for precise fitting of
the assembly. Some of the complex parts viz., electronic control box, rotary
joint mechanisms, and sensor fixtures are manufactured using 3D printing
technique. The timing-belt mechanism is provided for the simultaneous
robot locomotion and adhesion using passive and active means while
climbing avoiding solenoid valves with each suction cup. The steering
mechanism exhibits sharp turning for complete coverage path planning
(CCPP) in a given facade geometry.
Electric hardware and software
The electronic system layout in various connections of the different electronic
components used for robot locomotion, steering, and adhesion force control for GFCR
motion trials. Here, two DC geared motors (Motor 1& 2) are used for timing-belt
locomotion.
A group of three motors (Motor 3, 4 & 5) is used for the steering motion of the robot. DC
geared motor (Motor-6) is used to rotate the roller brush of the robot while cleaning.
There are two relays for the vacuum control for the robot motion. When the robot uses
its steering mechanism, relay-2 actuates the DC solenoid valve-2 for the creation of
vacuum inside the round suction cups of the steering mechanism. When the robot
locomotion uses the two-timing belts, it uses the relay-1 to activate the DC solenoid
valve-1 for vacuum creation in oval suction cups. In this situation, we can also use the
active/passive attachment of steering suction cups for extra payload-carrying of the
GFCR.
The control hardware using Arduino Mega Atmega2560 micro-controller is devised for
the various control strategies such as locomotion, steering, adhesion force, and vacuum
control of the GFCR. Radio frequency (RF)wireless communication module is used to
communicate between the GFCR and the ground operator. The open-source Arduino
Software (IDE) is used to program the robot for experimental trials.
Conclusions
The present work describes a unique design concept of GFCR with efficient
path planning for cleaning a glass surface. The robot has been designed
using timing-belt, guide-rail and steering mechanisms with passive and
active suction for continuous locomotion and adhesion with sharp steering
for efficient coverage. The design study optimizes the power required to
control vacuum inside the multi-suction cups without implementing the
conventional solenoid valve approach which further limits the weight of the
robot to 200 N. The detailed 3D-CAD design provides the required robot
physical and geometrical parameters for the simulation work. The dynamic
modeling of the GFCR has been derived using Lagrange’s formulation along
with a hybrid PSO PID controlling approach for various trajectory tracking
and motion planning. The developed modified PSO algorithm for autotuning optimal PID gains exhibits efficient convergence characteristics
compared to the standard PSO in the tracking algorithms. The trajectory
tracking simulation using hybrid PID-PSO approach provides the relevant
information for efficient robot path planning, such as torque and power
requirements for robot implementation in real-time environments. An
efficient CCPP algorithm has also been developed and used to simulate four
different coverage paths, such as HLS, VLS, SLS, and SCD. The HLS downward
coverage path shows the most energy-efficient way of glass facade cleaning.
Both the simulations and experimental findings show a close correlation
and validate the proposed robot motion
simulation strategies. Additional adhesion force using active suction in the
timing-belt and steering mechanisms will be further investigated and
compared with the passive suction-based climbing.
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