{"title":"微创手术中安全的内窥镜保持:零刚度和适应性重量补偿","authors":"Jesus Mago, F. Louveau, M. Vitrani, G. Morel","doi":"10.1109/icra46639.2022.9811359","DOIUrl":null,"url":null,"abstract":"One of the major functions brought by robots in Minimally Invasive Surgery is endoscope holding. This consists, for the user, in placing the camera at a desired location which the robot will maintain still once he/she releases it. This behavior is usually achieved with rigid position servoing, leading to possibly high forces generated and safety issues. Model-based weight compensation is an alternative solution. However, endoscopic cameras' weight is difficult to model as their gravity parameters can change during the same surgery. In this paper, an algorithm is presented as an option to cope with this variability in the gravity model without using rigid position servoing. The surgeon first positions the camera in a comanipulation mode (gravity compensation). When he/she releases the camera, if the gravity model is not accurate, the endoscope presents a drift. In this case, a controller brings the endoscope back to its release position by combining low gain position control and model adaptation. Once stabilized, the system is switched back to a zero-stiffness mode. Two in-vitro experiments were performed in which a user manipulates an endoscope whose configuration of mass is changed. In one case, the mass in the gravity model was set to half of the actual one. In the second case, a variable weight was attached to the endoscope. The algorithm successfully updated the model for each experiment reducing position errors by 95% and 57%, respectively.","PeriodicalId":341244,"journal":{"name":"2022 International Conference on Robotics and Automation (ICRA)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Safe endoscope holding in minimally invasive surgery: zero stiffness and adaptive weight compensation\",\"authors\":\"Jesus Mago, F. Louveau, M. Vitrani, G. Morel\",\"doi\":\"10.1109/icra46639.2022.9811359\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"One of the major functions brought by robots in Minimally Invasive Surgery is endoscope holding. This consists, for the user, in placing the camera at a desired location which the robot will maintain still once he/she releases it. This behavior is usually achieved with rigid position servoing, leading to possibly high forces generated and safety issues. Model-based weight compensation is an alternative solution. However, endoscopic cameras' weight is difficult to model as their gravity parameters can change during the same surgery. In this paper, an algorithm is presented as an option to cope with this variability in the gravity model without using rigid position servoing. The surgeon first positions the camera in a comanipulation mode (gravity compensation). When he/she releases the camera, if the gravity model is not accurate, the endoscope presents a drift. In this case, a controller brings the endoscope back to its release position by combining low gain position control and model adaptation. Once stabilized, the system is switched back to a zero-stiffness mode. Two in-vitro experiments were performed in which a user manipulates an endoscope whose configuration of mass is changed. In one case, the mass in the gravity model was set to half of the actual one. In the second case, a variable weight was attached to the endoscope. The algorithm successfully updated the model for each experiment reducing position errors by 95% and 57%, respectively.\",\"PeriodicalId\":341244,\"journal\":{\"name\":\"2022 International Conference on Robotics and Automation (ICRA)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Robotics and Automation (ICRA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icra46639.2022.9811359\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Robotics and Automation (ICRA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icra46639.2022.9811359","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Safe endoscope holding in minimally invasive surgery: zero stiffness and adaptive weight compensation
One of the major functions brought by robots in Minimally Invasive Surgery is endoscope holding. This consists, for the user, in placing the camera at a desired location which the robot will maintain still once he/she releases it. This behavior is usually achieved with rigid position servoing, leading to possibly high forces generated and safety issues. Model-based weight compensation is an alternative solution. However, endoscopic cameras' weight is difficult to model as their gravity parameters can change during the same surgery. In this paper, an algorithm is presented as an option to cope with this variability in the gravity model without using rigid position servoing. The surgeon first positions the camera in a comanipulation mode (gravity compensation). When he/she releases the camera, if the gravity model is not accurate, the endoscope presents a drift. In this case, a controller brings the endoscope back to its release position by combining low gain position control and model adaptation. Once stabilized, the system is switched back to a zero-stiffness mode. Two in-vitro experiments were performed in which a user manipulates an endoscope whose configuration of mass is changed. In one case, the mass in the gravity model was set to half of the actual one. In the second case, a variable weight was attached to the endoscope. The algorithm successfully updated the model for each experiment reducing position errors by 95% and 57%, respectively.