Harvesting represents the crucial stage in the cultivation process of Agaricus bisporus mushrooms.An important way for the production process of Agaricus bisporus to reduce costs and increase income is to ensure timel...Harvesting represents the crucial stage in the cultivation process of Agaricus bisporus mushrooms.An important way for the production process of Agaricus bisporus to reduce costs and increase income is to ensure timely harvest of Agaricus bisporus,reduce harvesting costs,and improve harvesting efficiency.There are many disadvantages in manual picking,such as high labor intensity,time-consuming work and high cost.In this study,a set of mushroom picking platform including climbing mechanism,picking robot,and control system was designed and developed.The picking robot consisted of a truss mechanism,an image acquisition device,a mushroom collection device,and a picking actuator.The profile picking actuator could realize the function of constant force clamping.An online size detection algorithm for Agaricus bisporus based on deep image processing was proposed.The algorithm included removal of abnormal noise points,background segmentation,coordinate conversion,and diameter detection.The precision picking system for Agaricus bisporus with coordinate compensation function controlled by Industrial Personal Computer was designed,and the visual control interface was developed based on Labview.Through the performance test,the reliability of machine vision recognition and the overall operating stability of the picking platform were verified.The test results showed that in the process of machine vision recognition,the recognition accuracy rate was higher than 92.50%,the missed detection rate was lower than 4.95%,the false detection rate was lower than 2.15%,and the diameter measurement error was less than 4.50%.The image processing algorithm had high recognition rate and small diameter measurement error,which could meet the requirements of picking operation.The picking platform’s picking success rate was higher than 95.45%,the picking damage rate was lower than 3.57%,and the picking output rate was higher than 87.09%.Compared with manual picking,the recognition accuracy rate of the picking platform was increased by 6.70%,the picking output rate was increased by 1.51%.The overall performance of the picking platform was stable and practical.展开更多
The manufacture and maintenance of large parts in ships,trains,aircrafts,and so on create an increasing demand for mobile machine tools to perform in-situ operations.However,few mobile robots can accommodate the compl...The manufacture and maintenance of large parts in ships,trains,aircrafts,and so on create an increasing demand for mobile machine tools to perform in-situ operations.However,few mobile robots can accommodate the complex environment of industrial plants while performing machining tasks.This study proposes a novel six-legged walking machine tool consisting of a legged mobile robot and a portable parallel kinematic machine tool.The kinematic model of the entire system is presented,and the workspace of different components,including a leg,the body,and the head,is analyzed.A hierarchical motion planning scheme is proposed to take advantage of the large workspace of the legged mobile platform and the high precision of the parallel machine tool.The repeatability of the head motion,body motion,and walking distance is evaluated through experiments,which is 0.11,1.0,and 3.4 mm,respectively.Finally,an application scenario is shown in which the walking machine tool steps successfully over a 250 mmhigh obstacle and drills a hole in an aluminum plate.The experiments prove the rationality of the hierarchical motion planning scheme and demonstrate the extensive potential of the walking machine tool for in-situ operations on large parts.展开更多
基金supported by the National Key Research and Development Program of China(Grant No.2023YFD2001100)the Major Science and Technology Programs of Henan Province(Grant No.221100110800)the Henan Provincial Major Science and Technology Special Project(Longmen Laboratory First-Class Project,Grant No.231100220200).
文摘Harvesting represents the crucial stage in the cultivation process of Agaricus bisporus mushrooms.An important way for the production process of Agaricus bisporus to reduce costs and increase income is to ensure timely harvest of Agaricus bisporus,reduce harvesting costs,and improve harvesting efficiency.There are many disadvantages in manual picking,such as high labor intensity,time-consuming work and high cost.In this study,a set of mushroom picking platform including climbing mechanism,picking robot,and control system was designed and developed.The picking robot consisted of a truss mechanism,an image acquisition device,a mushroom collection device,and a picking actuator.The profile picking actuator could realize the function of constant force clamping.An online size detection algorithm for Agaricus bisporus based on deep image processing was proposed.The algorithm included removal of abnormal noise points,background segmentation,coordinate conversion,and diameter detection.The precision picking system for Agaricus bisporus with coordinate compensation function controlled by Industrial Personal Computer was designed,and the visual control interface was developed based on Labview.Through the performance test,the reliability of machine vision recognition and the overall operating stability of the picking platform were verified.The test results showed that in the process of machine vision recognition,the recognition accuracy rate was higher than 92.50%,the missed detection rate was lower than 4.95%,the false detection rate was lower than 2.15%,and the diameter measurement error was less than 4.50%.The image processing algorithm had high recognition rate and small diameter measurement error,which could meet the requirements of picking operation.The picking platform’s picking success rate was higher than 95.45%,the picking damage rate was lower than 3.57%,and the picking output rate was higher than 87.09%.Compared with manual picking,the recognition accuracy rate of the picking platform was increased by 6.70%,the picking output rate was increased by 1.51%.The overall performance of the picking platform was stable and practical.
基金Funded by the National Natural Science Foundation of China(Grant No.U1613208)the National Key Research and Development Plan of China(Grant No.2017YFE0112200)the European Union’s Horizon 2020 Research and Innovation Programme under the Marie Skłodowska-Curie grant agreement No.734575.
文摘The manufacture and maintenance of large parts in ships,trains,aircrafts,and so on create an increasing demand for mobile machine tools to perform in-situ operations.However,few mobile robots can accommodate the complex environment of industrial plants while performing machining tasks.This study proposes a novel six-legged walking machine tool consisting of a legged mobile robot and a portable parallel kinematic machine tool.The kinematic model of the entire system is presented,and the workspace of different components,including a leg,the body,and the head,is analyzed.A hierarchical motion planning scheme is proposed to take advantage of the large workspace of the legged mobile platform and the high precision of the parallel machine tool.The repeatability of the head motion,body motion,and walking distance is evaluated through experiments,which is 0.11,1.0,and 3.4 mm,respectively.Finally,an application scenario is shown in which the walking machine tool steps successfully over a 250 mmhigh obstacle and drills a hole in an aluminum plate.The experiments prove the rationality of the hierarchical motion planning scheme and demonstrate the extensive potential of the walking machine tool for in-situ operations on large parts.
