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Smurf: a fully autonomous water surface cleaning robot with a novel coverage path planning method.

water cleaning boat research paper

1. Introduction

  • We design a new robot that achieves fully autonomous water surface cleaning and significantly increases cleaning efficiency.
  • We propose a novel CPP method for water surface cleaning and design an improved NMPC for water surface cleaning robots.
  • We conduct real-world experiments in various water bodies to test the cleaning performance of SMURF.

2. Related Work

2.1. water surface robot, 2.2. coverage path planning, 3. water surface cleaning robot design, 3.1. hull design, 3.2. hardware, 3.3. working procedure, 4. autonomous system, 4.1. autonomous system framework, 4.2. water surface coverage path planning.

The WSCPP algorithm (for regular region).
Regular region with coordinates of boundary points in the region , width of single effective cleaning d
Optimal trajectory
  1: Define set of trajectories
  2: 
  3:       Compute the scan direction parallel to edge line
  4:       Generate multiple lines by translating line by space d until there are no more parallel line intersecting with the region edges. The generated set of lines
  5:       Define back-and-forth trajectory line set
  6:           
  7:             Calculate the intersection point set between and region edges
  8:                 
  9:                   Inverse points sequence
10:             
11:             Add into
12:       
13:       Add into W
14: 
15: 
The WSCPP algorithm (for irregular region).
Irregular region with coordinates of boundary points in the region } width of single effective cleaning d, obstacle set
Optimal trajectory
  1: 
  2: Combine the points in with points in as point set P
  3: Apply triangulation to P and get triangle set [ ]. Delete the triangles that are contained in the obstacles, and get the final triangle set T
  4: Combine triangles in set T into multiple convex polygons, and get the sub-region set
  5: Choose the sub-region that contains original boundary points and closest to the start point of the robot as the first sub-region , and .
  6: 
  7:       Delete from B
  8:       Generate coverage planning path using Algorithm 1.
  9:           
10:              Define line x as the line connecting the end point of to the first point of .
11:              Get all the obstacles that have intersection points with x, and sort the obstacles from the shortest to the longest according to their distances to the end point of , and obstacles set is .
12:              Define the path bypassing the obstacles as u
13:                  
14:                    Calculate the intersection points of x and
15:                    Divide the boundary of into two parts by points
16:                     both and are inside of the region  
17:                          Add the shorter one of and into u
18:                    
19:                          Add one of and that is inside of the region into u
20:                    
21:                    Add u into
22:              
23:       
24:       Add trajectory point set into
25:        there are sub-regions adjacent in B 
26:              Set as the sub-region adjacent and closest to the end point of .
27:       
28:              Set as the sub-region closest to the end point of .
29:       
30: 

4.3. Improved NMPC

  • In the process of operation, the mass of SMURF increases when collecting garbage, namely, M , C , D , g ( η ) are time-varying matrix.
  • In the garbage collection process, the distribution of garbage in the trash container is unknown. The nonlinear resistance matrix D will change, which will cause an obvious deviation.
  • Over time, the motor will age and wear out, which will result in a lower control input force τ .

5. Experiment and Evaluation

5.1. water surface coverage path planning, 5.2. trajectory tracking evaluation, 5.3. water surface cleaning performance evaluation, 6. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest, abbreviations.

CPPCoverage Path Planning
GNSSGlobal Navigation Satellite System
IMUInertial Measurement Unit
mmWaveMillimeter Wave Radar
NMPCNonlinear Model Predictive Controller
USVUnmanned Surface Vehicle
UAVUnmanned Aerial Vehicles
WSCPPWater Surface Coverage Path Planning
RTKReal-Time Kinematic
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Click here to enlarge figure

ItemsCharacteristics
Length × Height × Width2.5 m × 1.6 m × 0.8 m
Weight100 kg
Trash Payload40 kg
Maximum Speed1.6 m/s
Height of Center of Gravity0.25 m
ItemsCharacteristics
Main processorNvidia Xavier NX
SensorRGB camera, mmWave radar, GNSS, IMU
Power Supply24 V 140 AH lithium battery
Control ModeAutomatic / 2.4 G Wireless / 4 G Network
Running Time8 h
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Share and Cite

Zhu, J.; Yang, Y.; Cheng, Y. SMURF: A Fully Autonomous Water Surface Cleaning Robot with A Novel Coverage Path Planning Method. J. Mar. Sci. Eng. 2022 , 10 , 1620. https://doi.org/10.3390/jmse10111620

Zhu J, Yang Y, Cheng Y. SMURF: A Fully Autonomous Water Surface Cleaning Robot with A Novel Coverage Path Planning Method. Journal of Marine Science and Engineering . 2022; 10(11):1620. https://doi.org/10.3390/jmse10111620

Zhu, Jiannan, Yixin Yang, and Yuwei Cheng. 2022. "SMURF: A Fully Autonomous Water Surface Cleaning Robot with A Novel Coverage Path Planning Method" Journal of Marine Science and Engineering 10, no. 11: 1620. https://doi.org/10.3390/jmse10111620

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IoT Based Water Surface Cleaning and Quality Checking Boat

B. Saran Raj 1 , L. Murali 1 , B. Vijayaparamesh 1 , J. Sharan Kumar 1 and P. Pragadeesh 1

Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series , Volume 1937 , International Conference on Novel Approaches and Developments in Biomedical Engineering-2021 (ICNADBE 2021) 22-23 April 2021, Coimbatore, India Citation B. Saran Raj et al 2021 J. Phys.: Conf. Ser. 1937 012023 DOI 10.1088/1742-6596/1937/1/012023

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1 P. A. College of Engineering and Technology, Pollachi-642002, Tamil Nadu, India

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It is foremost important to keep the water bodies around us to be clean. It is very terrible that huge amount of garbage is deposited on water bodies every year. Monitoring the quality of water that is present in the water bodies is also very important in today's world. There is a group of people who keep on monitoring the changes that occurs on the surroundings who are named as Catchment Management Authorities. Catchment Management Authorities monitor and provide real-time day to day updates on environmental protection and tracking pollution sources. A cheap non-wired aquatic monitoring system will enable cost effective water quality measurement by collecting data as well as assisting catchment managers to maintain the health of aquatic ecosystem. The work deals with finding a way for the uncertain effects of the floating particles, hence reducing the harmfulness created on behalf of the floating particles that incorporates floating materials and curbs. Our work aims to create a garbage gathering object to monitor the lakes and ponds and also measure the condition of water by measuring several parameters. In addition, it helps to understand the water pollution using data analysis. The main feature of this project is to collect of floating objects from the surface of the water into a trash container. The Secondary work of our project is to measure the water quality by using sensors, by measuring the water quality parameters we can be able to predict the unfavourable conditions of water living creatures. pH Sensor and Turbidity Sensor are used in our project to measure the acidity and basicity of the water and turbidity level of the water respectively. The main motto is to clean the surface of the water and check the quality of the water which helps for aquatic ecosystem.

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