著者

成田 結香

出版者

法政大学大学院理工学研究科

雑誌

法政大学大学院紀要. 理工学・工学研究科編 (ISSN:21879923)

巻号頁・発行日

vol.60, pp.1-7, 2019-03-31

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Laparoscopic surgery is a difficult surgical procedure as compared with open operation. Therefore, training is necessary for surgeons before conducting laparoscopic surgery clinically. In this paper, improvement and extension of the training system which has been developed by our group was carried out. First, effectiveness of the evaluation method for trainee's hands movement was verified through the past measurement data obtained for operation of ligation. Second, in order to make it easy to perform ligation under Para-axial position, camera position of the training box was improved. Third, former sensor module which was attached to the forceps was downsized so as not to collide to other objects. Finally, the proposed evaluation system for hands movement and the evaluation system for angle of the wrists which was developed in our previous study were merged. Then, the evaluation results of trainee's angle of the left and the right wrists, hands movement and operation time in comparison with those of the excellent skilled surgeon are displayed on the monitor screen.

著者

四木 宏香

出版者

法政大学大学院理工学研究科

雑誌

法政大学大学院紀要. 理工学・工学研究科編 (ISSN:21879923)

巻号頁・発行日

vol.61, pp.1-6, 2020-03-24

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The multi-map navigation using SLAM is one of the current research topics of the mobile robots. In this paper, we describe a study of a mobile robot navigation using the multi-map method. By applying SLAM, both the map and trajectory of a mobile robot can be generated simultaneously. However, the drawback of SLAM depends on sensor accuracy, which may cause mapping failure. One of the solutions to prevent the failure of mapping is not monolithic mapping but short-term multiple mapping. The advantage of short-term multiple map generation can reduce map construction failures. The other typical applications for multi-map is multi-floor navigation. In this paper, we apply multi-map method for both navigations. The usefulness of the proposed method was confirmed by simulation and actual experiments.

著者

河野 辰哉

出版者

法政大学大学院理工学研究科

雑誌

法政大学大学院紀要. 理工学・工学研究科編 (ISSN:21879923)

巻号頁・発行日

vol.60, pp.1-6, 2019-03-31

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This paper describes the development of Robot Operating System (ROS) component for lane recognition and navigation of IGVC Auto - Nav Challenge. To achieve a robust and stable navigation, we propose new lane and obstacle recognition algorithm based on omnidirectional camera. Employing fast NCC based piecewise template matching technique enables robust lane detection regardless of surrounding brightness changes and various lane shape including sharp curves. To recognize surrounding obstacles only vision sensor without LiDAR, we employ YOLOv3-tiny based deep learning algorithm which can avoid obstacle collision. Since ROS has capability of environmental simulation by using Gazebo, rapid prototyping is achieved by applying both simulations and actual experiments which can significantly reduce development period. The effectiveness of the newly proposed algorithm was confirmed by both offline simulation and actual outdoor experiment.

著者

伊藤 千鶴

出版者

法政大学大学院理工学研究科

雑誌

法政大学大学院紀要. 理工学・工学研究科編 (ISSN:21879923)

巻号頁・発行日

vol.59, pp.1-4, 2018-03-31

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We can imagine that one having more useful information gets superior than others if they are in the same condition and under some struggling situation. For example, in a supermarket, we naturally choose the shortest queue of cashiers in order to finish our payment with minimal waiting time. If one knows a better strategy to choose the queue, she or he can finish the payment in more shorter time. However, the more customers know the strategy, the less the effectiveness of using the strategy. In this study, we assume one strategy in such a situation, and investigate its effectiveness via simulation study.

著者

横林 亮平

出版者

法政大学大学院理工学研究科

雑誌

法政大学大学院紀要. 理工学・工学研究科編 (ISSN:21879923)

巻号頁・発行日

no.60, pp.1-8, 2019-03-31

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The tensor data model is capable of detailed data representation and is compatible with data mining. However, there is a problem that the data volume becomes enormous and processing time is required. It is one solution to this problem to improve the efficiency of a series of data processing such as insertion, deletion, search of data in the secondary storage area. In this paper, we propose an serial search method using locality sensitive hashing. The hash technique is a search method that is hardly affected by the data amount, but there is a problem that the serial search can not be performed. By using locality sensitive hashing, we sequentially arrange similar data in the same block and improve efficiency by carrying out parallel processing for each block. We will also describe the efficiency of tensor data manipulation (especially data mining manipulation). Using locality sensitive hashing, realize high-speed multidimensional association rules extraction limited to partial data.