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A complete coverage path planning Algorithm for Lawn Mowing Robots Based on Deep Reinforcement Learning

SENSORS 2025年第2期25卷 416-416页

作者： Chen, Ying Lu, Zhe-Ming Cui, Jia-Lin Luo, Hao Zheng, Yang-Ming Huanjiang Lab Ctr Gener Aerosp Technol Zhuji 311816 Peoples R China Zhejiang Univ Sch Aeronaut & Astronaut Hangzhou 310027 Peoples R China NingboTech Univ Sch Informat Sci & Engn Ningbo 315100 Peoples R China

This paper introduces Re-DQN, a deep reinforcement learning-based algorithm for comprehensive coverage path planning in lawn mowing robots. In the fields of smart homes and agricultural automation, lawn mowing robots are rapidly gaining popularity to reduce the demand for manual labor. The algorithm introduces a new exploration mechanism, combined with an intrinsic reward function based on state novelty and a dynamic input structure, effectively enhancing the robot's adaptability and path optimization capabilities in dynamic environments. In particular, Re-DQN improves the stability of the training process through a dynamic incentive layer and achieves more comprehensive area coverage and shorter planning times in high-dimensional continuous state spaces. Simulation results show that Re-DQN outperforms the other algorithms in terms of performance, convergence speed, and stability, making it a robust solution for comprehensive coverage path planning. Future work will focus on testing and optimizing Re-DQN in more complex environments and exploring its application in multi-robot systems to enhance collaboration and communication.

关键词： path planning complete coverage path planning reward function curiosity-driven exploration dynamic epsilon-greedy strategy dynamic environments training stability

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complete coverage path planning for wheeled agricultural robots

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JOURNAL OF FIELD ROBOTICS 2023年第6期40卷 1460-1503页

作者： Arab, Danial Pour Spisser, Matthias Essert, Caroline Univ Strasbourg ICube CNRS UMR 7357 300 Bd Sebastien Brant F-67400 Illkirch Graffenstaden France T&S Technol & Strategy Strasbourg Schiltigheim France

In the agricultural industry, an evolutionary effort has been made over the last two decades to achieve precise autonomous systems to perform typical in-field tasks, including harvesting, mowing, and spraying. One of the main objectives of an autonomous system in agriculture is to improve the efficiency while reducing the environmental impact and cost. Due to the nature of these operations, complete coverage path planning (CCPP) approaches play an essential role to find an optimal path which covers the entire field while taking into account land topography, operation requirements, and robot characteristics. The aim of this paper is to propose a CCPP approach defining the optimal movements of mobile robots over an agricultural field. First, a method based on tree exploration is proposed to find all potential solutions satisfying some predefined constraints. Second, a similarity check and selection of optimal solutions method is proposed to eliminate similar solutions and find the best solutions. The optimization goals are to maximize the coverage area and to minimize overlaps, nonworking path length, and overall travel time. To explore a wide range of possible solutions, our approach is able to consider multiple entrances for the robot. For fields with a complex shape, different dividing lines to split them into simple polygons are also considered. Our approach also computes the headland zones and covers them automatically which leads to a high coverage rate of the field.

关键词： autonomous agriculture complete coverage path planning path planning precision agriculture route planning vehicle routing problem wheeled robots

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complete coverage path planning and performance factor analysis for autonomous bulldozer

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JOURNAL OF FIELD ROBOTICS 2022年第7期39卷 1014-1034页

作者： Li, Rao Zhou, Cheng Dou, Quanli Hu, Bin Huazhong Univ Sci & Technol Natl Ctr Technol Innovat Digital Construct Wuhan Hubei Peoples R China Huazhong Univ Sci & Technol Sch Civil & Hydraul Engn Dept Construct Management Wuhan Hubei Peoples R China Weichai Power Co Ltd Weifang Shandong Peoples R China Shantui Construct Machinery Co Ltd Jining Shandong Peoples R China

With the development of intelligent machinery, path planning of autonomous bulldozers plays an important role to solve the problems of efficiency in future construction sites. How to plan the path that meets the construction requirements is the key problem. This study investigates the standardized construction workmanship and moving rules of the bulldozer to add rules and path selection strategies to the algorithm. This study establishes the path planning model of bulldozer's leveling, considering the limitations of the traditional bioinspired neural network algorithm, an improved complete coverage path planning method is proposed. An integrated framework is proposed for an automatic bulldozer with a sensor system for a field experiment to verify the feasibility of the method. According to the comparative statistical simulation results, the effectiveness of the method is verified, and the effects of different factors on the path planning results are analyzed.

关键词： autonomous bulldozer BINN hybrid A* algorithm complete coverage path planning earthwork construction performance factors analysis sensor system site layout

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complete coverage path planning of Autonomous Underwater Vehicle Based on GBNN Algorithm

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JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 2019年第1期94卷 237-249页

作者： Zhu, Daqi Tian, Chen Sun, Bing Luo, Chaomin Shanghai Maritime Univ Lab Underwater Vehicles & Intelligent Syst Haigang Ave 1550 Shanghai 201306 Peoples R China Univ Detroit Mercy Dept Elect & Comp Engn Detroit MI 48221 USA

For the shortcomings of biologically inspired neural network algorithm in the path planning of robots, such as high computational complexity, long path planning time etc Glasius Bio-inspired Neural Network (GBNN) algorithm is proposed to improve the algorithm, and applied to the complete coverage path planning of autonomous underwater vehicle (AUV). Firstly, the grid map is constructed by discretizing the two-dimensional underwater environment. Secondly, the corresponding dynamic neural network is built on the grid map. Finally, complete coverage path of AUV is planned based on the GBNN strategy and the path of AUV at the edge of obstacles is optimized by some typical path templates. The simulation results show that the AUV can completely cover the entire workspace and immediately escape from deadlocks without any waiting. Meanwhile, the efficiency of complete coverage path planning is high with short path planning time and low overlapping coverage rate by using the algorithm proposed in this paper.

关键词： Autonomous underwater vehicle (AUV) complete coverage path planning GBNN algorithm Neural network

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complete coverage path planning for Multi-Robots Based on

Complete Coverage Path Planning for Multi-Robots Based on

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11th International Conference on Control, Automation and Systems (ICCAS)/Robot World Conference

作者： Janchiv, Adiyabaatar Batsaikhan, Dugarjav Kim, Gook Hwan Lee, Soon-Geul Kyung Hee Univ Dept Mech Engn Yongin 449701 Gyeonggi Do South Korea

ISBN: (纸本)9788993215038

complete coverage path planning is major problem for autonomous mobile robot, which concerns both efficiency and completeness of coverage. In this paper, a complete coverage path planning algorithm is proposed for two indoor floor-caring robots, such as cleaning or inspecting industrial and public floor areas, to have the minimal turning path based on the shape and size of the cell covering the whole working area. The proposed algorithm divides the whole cleaning area into cells by cellular decomposition method, and then provides efficient covering order over the cells based on distance among centroids of cells. It also provides more optimal coverage path and reduces the rate of energy consumption and working time. Both simulation and experimental results demonstrate the effectiveness of the algorithm. As compared performance indices between experiment and simulation, the total number of turns and the working time show the practical efficiency and robustness of the proposed algorithm.

关键词： complete coverage path planning Cellular Decomposition Cleaning Robot Multi-robot robustness

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complete coverage path planning for Data Collection with Multiple UAVs 25

Complete Coverage Path Planning for Data Collection with Mul...

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IEEE Wireless Communications and Networking Conference (IEEE WCNC)

作者： Chen, Yuhong Mou, Zhiyu Lin, Bo Zhang, Tengyu Gao, Feifei Tsinghua Univ Dept Automat BNRist Beijing 100084 Peoples R China

ISBN: (纸本)9798350303582;9798350303599

The utilization of unmanned aerial vehicles (UAVs) for communication data collection across all areas can be modeled as a complete coverage path planning (CCPP) problem. To address the challenge of lengthy coverage time in traditional CCPP algorithms, we propose a weighted balanced graph partitioning based complete coverage path planning scheme (WBGPP), which consists of two sub-algorithm: weighted balanced graph partitioning (Weighted B-GRAP) and single agent path planning (SAPP). The Weighted B-GRAP algorithm can decompose the multi-UAV CCPP problem into multiple single UAV CCPP problems by assigning each UAV a responsibility area according to its capability. Then, we optimize the backtracking strategy through breadth-first search and design a SAPP algorithm to reduce the number of repeated visits and shorten the coverage time. The simulation results show that the proposed WBGPP scheme effectively reduce the coverage time of multiple UAVs in CCPP problems and can be applied to various maps.

关键词： complete coverage path planning multi-agent UAV weighted balanced graph partition transferability

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complete coverage path planning of wall-cleaning robot using visual sensor

Complete coverage path planning of wall-cleaning robot using...

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8th International Conference on Electronic Measurement and Instruments

作者： Wang Meiting Tan Shili Ding Junjian Yan Liwen Shanghai Univ Coll Mech Engn & Automat Shanghai 200072 Peoples R China

ISBN: (纸本)1424411351

A design and implication of a complete coverage path planning system based on visual sensor for wall-climbing robot is proposed in this paper. The visual sensor composed of an oriented CCD camera and two laser diodes helps robot align with walls and keep the robot stay in the planned path. The robot also can real-time inspect the obstacles on the planned path and carry out the obstacle avoidance manner with the help of visual sensor, thus the robot can complete the cleaning task efficiently in an environment with unexpected static obstacles. The wall-cleaning robot adopts a complete coverage cleaning strategy and executes back-and-forth cleaning task.. The experiment on complete coverage path planning and the motion control system has been carried out in order to examine the performance of the proposed navigation design based on visual sensors. The experimental results verify the effectiveness of the proposed approach.

关键词： wall-cleaning robot complete coverage path planning obstacle avoidance visual sensor

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complete coverage path planning for Multi-Robots Employing Flow Networks

Complete Coverage Path Planning for Multi-Robots Employing F...

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International Conference on Control, Automation and Systems

作者： Nam, Sang-Hyun Shin, Ik-Sang Kim, Jae-Jun Lee, Soon-Geul Cheongju Univ Elect & Informat Engn Dept Cheongju South Korea Kyung Hee Univ Dept Engn Mech Yongin South Korea

ISBN: (纸本)9788995003893

This paper describes a path planning algorithm, which is the minimal turning path based on the shape and size of the cell to clean up the whole area with two cleaning robots. Our method divides the whole cleaning area with each cell by cellular decomposition, and then provides some path plans among of the robots to reduce the rate of energy consumption and cleaning time of it. In addition we suggest how to plan between the robots especially when they are cleaning in the same cell. Finally simulation results demonstrate the effectiveness of the algorithm in an unknown area with multiple robots. And then we compare the performance index of two algorithms such as total of turn, total of time.

关键词： complete coverage path planning Cellular Decomposition Cleaning Robot Multi-robot

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complete coverage path planning for an Arnold system based mobile robot to perform specific types of missions

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Frontiers of Information Technology & Electronic Engineering 2019年第11期20卷 1530-1542页

作者： Cai-hong LI Chun FANG Feng-ying WANG Bin XIA Yong SONG College of Computer Science and Technology Shandong University of TechnologyZibo 255000China School of Mechanical Electrical&Information EngineeringShandong UniversityWeihai 264209China

We propose a contraction transformation algorithm to plan a complete coverage trajectory for a mobile robot to ac-complish specific types of missions based on the Arnold dynamical system. First, we construct a chaotic mobile robot by com-bining the variable z of the Arnold equation and the kinematic equation of the robot. Second, we construct the candidate sets including the initial points with a relatively high coverage rate of the constructed mobile robot. Then the trajectory is contracted to the current position of the robot based on the designed contraction transformation strategy, to form a continuous complete cov-erage trajectory to execute the specific types of missions. Compared with the traditional method, the designed algorithm requires no obstacle avoidance to the boundary of the given workplace, possesses a high coverage rate, and keeps the chaotic characteristics of the produced coverage trajectory relatively unchanged, which enables the robot to accomplish special missions with features of completeness, randomness, or unpredictability.

关键词： Chaotic mobile robot Arnold dynamical system Contraction transformation complete coverage path planning Candidate set

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complete coverage path planning Based on Ant Colony Algorithm

Complete Coverage Path Planning Based on Ant Colony Algorith...

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15th International Conference on Mechatronics and Machine Vision in Practice

作者： Zhang Chibin Wang Xingsong Du Yong Southeast Univ Sch Mech Engn Nanjing 211189 Peoples R China

ISBN: (纸本)9781424437795

The complete coverage path planning algorithm integrating local sub-area coverage with global planning was proposed. According to the characteristic of Boustrophedon cellular decomposition, the robot covers local sub-area through back and forth motion. The distance between every sub-areas was redefined, which including connectivity, least distance and number of obstacles between sub-areas. The new distance matrix of sub-areas in environment is built for global planning. Based on ant colony algorithm, the robot uses the distance matrix to get the optimization sequence of the sub-areas after decomposed the coverage environment. Experiments on a simulation of environment verify the validity of the proposed algorithm.

关键词： mobile robot complete coverage path planning ant colony algorithm complete weighted connected matrix

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