Pub Date : 2021-01-25DOI: 10.1186/s40648-021-00202-8
Antonio Gabas, Y. Kita, E. Yoshida
{"title":"Dual edge classifier for robust cloth unfolding","authors":"Antonio Gabas, Y. Kita, E. Yoshida","doi":"10.1186/s40648-021-00202-8","DOIUrl":"https://doi.org/10.1186/s40648-021-00202-8","url":null,"abstract":"","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":"8 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2021-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65733973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-18DOI: 10.1186/s40648-021-00189-2
Natsumi Koike, T. Hayakawa
{"title":"Evaluation of the deformation shape of a balloon-type dielectric elastomer actuator prestretched with water pressure","authors":"Natsumi Koike, T. Hayakawa","doi":"10.1186/s40648-021-00189-2","DOIUrl":"https://doi.org/10.1186/s40648-021-00189-2","url":null,"abstract":"","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":"8 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2021-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40648-021-00189-2","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65733478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-01-07DOI: 10.1186/s40648-020-00188-9
Soheil Habibian, Mehdi Dadvar, Behzad Peykari, Alireza H. M. Hosseini, M. Salehzadeh, Alireza H. M. Hosseini, Farshid Najafi
{"title":"Design and implementation of a maxi-sized mobile robot (Karo) for rescue missions","authors":"Soheil Habibian, Mehdi Dadvar, Behzad Peykari, Alireza H. M. Hosseini, M. Salehzadeh, Alireza H. M. Hosseini, Farshid Najafi","doi":"10.1186/s40648-020-00188-9","DOIUrl":"https://doi.org/10.1186/s40648-020-00188-9","url":null,"abstract":"","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":"8 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2021-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40648-020-00188-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"65733398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-20DOI: 10.1186/s40648-020-00186-x
Taiki Abe, Y. Kawasaki, Kimitoshi Yamazaki
{"title":"A robotic end-effector with rolling up mechanism for pick-and-release of a cotton sheet","authors":"Taiki Abe, Y. Kawasaki, Kimitoshi Yamazaki","doi":"10.1186/s40648-020-00186-x","DOIUrl":"https://doi.org/10.1186/s40648-020-00186-x","url":null,"abstract":"","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40648-020-00186-x","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47183094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-19DOI: 10.1186/s40648-020-00185-y
Ayuko Saito, Satoru Kizawa, Yoshikazu Kobayashi, K. Miyawaki
{"title":"Pose estimation by extended Kalman filter using noise covariance matrices based on sensor output","authors":"Ayuko Saito, Satoru Kizawa, Yoshikazu Kobayashi, K. Miyawaki","doi":"10.1186/s40648-020-00185-y","DOIUrl":"https://doi.org/10.1186/s40648-020-00185-y","url":null,"abstract":"","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40648-020-00185-y","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47297406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-15DOI: 10.1186/s40648-020-00182-1
Kohei Kimura, Noriaki Imaoka, Shintaro Noda, Yohei Kakiuchi, K. Okada, M. Inaba
{"title":"Locomotion approach of bipedal robot utilizing passive wheel without swing leg based on stability margin maximization and fall prevention functions","authors":"Kohei Kimura, Noriaki Imaoka, Shintaro Noda, Yohei Kakiuchi, K. Okada, M. Inaba","doi":"10.1186/s40648-020-00182-1","DOIUrl":"https://doi.org/10.1186/s40648-020-00182-1","url":null,"abstract":"","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45460976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-10-13DOI: 10.1186/s40648-020-00184-z
Zhenyu Wang, G. Endo, Masashi Takahashi, Hiroyuki Nabae, K. Suzumori, N. Tsuzuki, H. Takahashi, K. Kimoto, T. Ihara, H. Kikura
{"title":"Study of a robotic system to detect water leakage and fuel debris-System proposal and feasibility study of visual odometry providing intuitive bird’s eye view-","authors":"Zhenyu Wang, G. Endo, Masashi Takahashi, Hiroyuki Nabae, K. Suzumori, N. Tsuzuki, H. Takahashi, K. Kimoto, T. Ihara, H. Kikura","doi":"10.1186/s40648-020-00184-z","DOIUrl":"https://doi.org/10.1186/s40648-020-00184-z","url":null,"abstract":"","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":" ","pages":""},"PeriodicalIF":1.4,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1186/s40648-020-00184-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41826683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-09-18DOI: 10.21203/rs.3.rs-78087/v1
Deepak Kumar, Sushil Raut, Kohei Shimasaki, T. Senoo, I. Ishii
The novel approach to physical security based on visible light communication (VLC) using an informative object-pointing and simultaneous recognition by high-framerate (HFR) vision systems is presented in this study. In the proposed approach, a convolutional neural network (CNN) based object detection method is used to detect the environmental objects that assist a spatiotemporal-modulated-pattern (SMP) based imperceptible projection mapping for pointing the desired objects. The distantly located HFR vision systems that operate at hundreds of frames per second (fps) can recognize and localize the pointed objects in real-time. The prototype of an artificial intelligence-enabled camera-projector (AiCP) system is used as a transmitter that detects the multiple objects in real-time at 30 fps and simultaneously projects the detection results by means of the encoded-480-Hz-SMP masks on to the objects. The multiple 480-fps HFR vision systems as receivers can recognize the pointed objects by decoding pixel-brightness variations in HFR sequences without any camera calibration or complex recognition methods. Several experiments were conducted to demonstrate our proposed method’s usefulness using miniature and real-world objects under various conditions.
{"title":"Projection-mapping-based object pointing using a high-frame-rate camera-projector system","authors":"Deepak Kumar, Sushil Raut, Kohei Shimasaki, T. Senoo, I. Ishii","doi":"10.21203/rs.3.rs-78087/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-78087/v1","url":null,"abstract":"The novel approach to physical security based on visible light communication (VLC) using an informative object-pointing and simultaneous recognition by high-framerate (HFR) vision systems is presented in this study. In the proposed approach, a convolutional neural network (CNN) based object detection method is used to detect the environmental objects that assist a spatiotemporal-modulated-pattern (SMP) based imperceptible projection mapping for pointing the desired objects. The distantly located HFR vision systems that operate at hundreds of frames per second (fps) can recognize and localize the pointed objects in real-time. The prototype of an artificial intelligence-enabled camera-projector (AiCP) system is used as a transmitter that detects the multiple objects in real-time at 30 fps and simultaneously projects the detection results by means of the encoded-480-Hz-SMP masks on to the objects. The multiple 480-fps HFR vision systems as receivers can recognize the pointed objects by decoding pixel-brightness variations in HFR sequences without any camera calibration or complex recognition methods. Several experiments were conducted to demonstrate our proposed method’s usefulness using miniature and real-world objects under various conditions.","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":"8 1","pages":"1-21"},"PeriodicalIF":1.4,"publicationDate":"2020-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43281525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-13DOI: 10.21203/rs.3.rs-51700/v1
M. Sanada, T. Matsuo, N. Shimada, Y. Shirai
In this study, a method for a robot to recall multiple grasping methods for a given object is proposed. The aim of this study was for robots to learn grasping methods for new objects by observing the grasping activities of humans in daily life without special instructions. For this setting, only one grasping motion was observed for an object at a time, and it was never known whether other grasping methods were possible for the object, although supervised learning generally requires all possible answers for each training input. The proposed method gives a solution for that learning situations by employing a convolutional neural network with automatic clustering of the observed grasping method. In the proposed method, the grasping methods are clustered during the process of learning of the grasping position. The method first recalls grasping positions and the network estimates the multi-channel heatmap such that each channel heatmap indicates one grasping position, then checks the graspability for each estimated position. Finally, the method recalls the hand shapes based on the estimated grasping position and the object’s shape. This paper describes the results of recalling multiple grasping methods and demonstrates the effectiveness of the proposed method.
{"title":"Recalling of multiple grasping methods from an object image with a convolutional neural network","authors":"M. Sanada, T. Matsuo, N. Shimada, Y. Shirai","doi":"10.21203/rs.3.rs-51700/v1","DOIUrl":"https://doi.org/10.21203/rs.3.rs-51700/v1","url":null,"abstract":"In this study, a method for a robot to recall multiple grasping methods for a given object is proposed. The aim of this study was for robots to learn grasping methods for new objects by observing the grasping activities of humans in daily life without special instructions. For this setting, only one grasping motion was observed for an object at a time, and it was never known whether other grasping methods were possible for the object, although supervised learning generally requires all possible answers for each training input. The proposed method gives a solution for that learning situations by employing a convolutional neural network with automatic clustering of the observed grasping method. In the proposed method, the grasping methods are clustered during the process of learning of the grasping position. The method first recalls grasping positions and the network estimates the multi-channel heatmap such that each channel heatmap indicates one grasping position, then checks the graspability for each estimated position. Finally, the method recalls the hand shapes based on the estimated grasping position and the object’s shape. This paper describes the results of recalling multiple grasping methods and demonstrates the effectiveness of the proposed method.","PeriodicalId":37462,"journal":{"name":"ROBOMECH Journal","volume":"8 1","pages":"1-13"},"PeriodicalIF":1.4,"publicationDate":"2020-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43101378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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