A. Nakazawa, K. Nanri, K. Harada, Shinichi Tanaka, H. Nukariya, Y. Kurose, Naoyuki Shono, Hirohumi Nakatomi, A. Morita, Eiju Watanabe, N. Sugita, M. Mitsuishi
{"title":"基于虚拟夹具的深、窄空间神经外科机器人避碰反馈方法","authors":"A. Nakazawa, K. Nanri, K. Harada, Shinichi Tanaka, H. Nukariya, Y. Kurose, Naoyuki Shono, Hirohumi Nakatomi, A. Morita, Eiju Watanabe, N. Sugita, M. Mitsuishi","doi":"10.1109/BIOROB.2016.7523632","DOIUrl":null,"url":null,"abstract":"Robotic assistance enables a surgeon to perform dexterous and precise manipulations. However, conducting robot assisted neurosurgery within the deep and narrow spaces of the brain presents the risk of unexpected collisions between the shafts of robotic instruments and their surroundings out of the microscopic view. Thus, we propose the provision of feedback using a truncated cone shaped virtual fixture generated by marking the edges of the top and bottom plane of a workspace in the deep and narrow spaces within the brain with the slave manipulator. The experimental results show that the virtual fixture generation method could precisely model the workspace. We also implemented force feedback, visual feedback, and motion scaling feedback in the microsurgical robotic system in order to inform the surgeon of the risk of collision. Performance of each feedback method and their combinations was evaluated in two experiments. The experimental results showed that the combination of the force and the visual feedback methods were the most beneficial for avoiding collisions.","PeriodicalId":235222,"journal":{"name":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2016-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Feedback methods for collision avoidance using virtual fixtures for robotic neurosurgery in deep and narrow spaces\",\"authors\":\"A. Nakazawa, K. Nanri, K. Harada, Shinichi Tanaka, H. Nukariya, Y. Kurose, Naoyuki Shono, Hirohumi Nakatomi, A. Morita, Eiju Watanabe, N. Sugita, M. Mitsuishi\",\"doi\":\"10.1109/BIOROB.2016.7523632\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Robotic assistance enables a surgeon to perform dexterous and precise manipulations. However, conducting robot assisted neurosurgery within the deep and narrow spaces of the brain presents the risk of unexpected collisions between the shafts of robotic instruments and their surroundings out of the microscopic view. Thus, we propose the provision of feedback using a truncated cone shaped virtual fixture generated by marking the edges of the top and bottom plane of a workspace in the deep and narrow spaces within the brain with the slave manipulator. The experimental results show that the virtual fixture generation method could precisely model the workspace. We also implemented force feedback, visual feedback, and motion scaling feedback in the microsurgical robotic system in order to inform the surgeon of the risk of collision. Performance of each feedback method and their combinations was evaluated in two experiments. The experimental results showed that the combination of the force and the visual feedback methods were the most beneficial for avoiding collisions.\",\"PeriodicalId\":235222,\"journal\":{\"name\":\"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIOROB.2016.7523632\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 6th IEEE International Conference on Biomedical Robotics and Biomechatronics (BioRob)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIOROB.2016.7523632","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feedback methods for collision avoidance using virtual fixtures for robotic neurosurgery in deep and narrow spaces
Robotic assistance enables a surgeon to perform dexterous and precise manipulations. However, conducting robot assisted neurosurgery within the deep and narrow spaces of the brain presents the risk of unexpected collisions between the shafts of robotic instruments and their surroundings out of the microscopic view. Thus, we propose the provision of feedback using a truncated cone shaped virtual fixture generated by marking the edges of the top and bottom plane of a workspace in the deep and narrow spaces within the brain with the slave manipulator. The experimental results show that the virtual fixture generation method could precisely model the workspace. We also implemented force feedback, visual feedback, and motion scaling feedback in the microsurgical robotic system in order to inform the surgeon of the risk of collision. Performance of each feedback method and their combinations was evaluated in two experiments. The experimental results showed that the combination of the force and the visual feedback methods were the most beneficial for avoiding collisions.