JP7637674B2 - 知覚システム - Google Patents
知覚システム Download PDFInfo
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- JP7637674B2 JP7637674B2 JP2022519454A JP2022519454A JP7637674B2 JP 7637674 B2 JP7637674 B2 JP 7637674B2 JP 2022519454 A JP2022519454 A JP 2022519454A JP 2022519454 A JP2022519454 A JP 2022519454A JP 7637674 B2 JP7637674 B2 JP 7637674B2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/42—Simultaneous measurement of distance and other co-ordinates
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
- G01S7/417—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section involving the use of neural networks
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/0088—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots characterized by the autonomous decision making process, e.g. artificial intelligence, predefined behaviours
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0257—Control of position or course in two dimensions specially adapted to land vehicles using a radar
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
- G06F18/2413—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches based on distances to training or reference patterns
- G06F18/24133—Distances to prototypes
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/0464—Convolutional networks [CNN, ConvNet]
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/0895—Weakly supervised learning, e.g. semi-supervised or self-supervised learning
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
- G06N3/09—Supervised learning
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/764—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using classification, e.g. of video objects
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
- G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/70—Labelling scene content, e.g. deriving syntactic or semantic representations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
- G01S15/88—Sonar systems specially adapted for specific applications
- G01S15/93—Sonar systems specially adapted for specific applications for anti-collision purposes
- G01S15/931—Sonar systems specially adapted for specific applications for anti-collision purposes of land vehicles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
- G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Theoretical Computer Science (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Health & Medical Sciences (AREA)
- Software Systems (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Computer Networks & Wireless Communication (AREA)
- Data Mining & Analysis (AREA)
- Computational Linguistics (AREA)
- Life Sciences & Earth Sciences (AREA)
- General Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Mathematical Physics (AREA)
- Biomedical Technology (AREA)
- Biophysics (AREA)
- Molecular Biology (AREA)
- Medical Informatics (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Aviation & Aerospace Engineering (AREA)
- Automation & Control Theory (AREA)
- Electromagnetism (AREA)
- Databases & Information Systems (AREA)
- Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Evolutionary Biology (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Acoustics & Sound (AREA)
- Traffic Control Systems (AREA)
- Radar Systems Or Details Thereof (AREA)
- Image Analysis (AREA)
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| US16/587,605 US11520037B2 (en) | 2019-09-30 | 2019-09-30 | Perception system |
| US16/587,605 | 2019-09-30 | ||
| PCT/US2020/051777 WO2021067056A1 (en) | 2019-09-30 | 2020-09-21 | Perception system |
Publications (3)
| Publication Number | Publication Date |
|---|---|
| JP2022549913A JP2022549913A (ja) | 2022-11-29 |
| JP2022549913A5 JP2022549913A5 (https=) | 2023-09-28 |
| JP7637674B2 true JP7637674B2 (ja) | 2025-02-28 |
Family
ID=72811935
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP2022519454A Active JP7637674B2 (ja) | 2019-09-30 | 2020-09-21 | 知覚システム |
Country Status (5)
| Country | Link |
|---|---|
| US (1) | US11520037B2 (https=) |
| EP (1) | EP4038408B1 (https=) |
| JP (1) | JP7637674B2 (https=) |
| CN (1) | CN114502979A (https=) |
| WO (1) | WO2021067056A1 (https=) |
Families Citing this family (28)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DK201970115A1 (en) | 2018-11-08 | 2020-06-09 | Aptiv Technologies Limited | Deep learning for object detection using pillars |
| WO2021016596A1 (en) | 2019-07-25 | 2021-01-28 | Nvidia Corporation | Deep neural network for segmentation of road scenes and animate object instances for autonomous driving applications |
| GB2591171B (en) * | 2019-11-14 | 2023-09-13 | Motional Ad Llc | Sequential fusion for 3D object detection |
| US11532168B2 (en) | 2019-11-15 | 2022-12-20 | Nvidia Corporation | Multi-view deep neural network for LiDAR perception |
| US12080078B2 (en) | 2019-11-15 | 2024-09-03 | Nvidia Corporation | Multi-view deep neural network for LiDAR perception |
| US11885907B2 (en) | 2019-11-21 | 2024-01-30 | Nvidia Corporation | Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications |
| US12050285B2 (en) | 2019-11-21 | 2024-07-30 | Nvidia Corporation | Deep neural network for detecting obstacle instances using radar sensors in autonomous machine applications |
| US11860634B2 (en) * | 2019-12-12 | 2024-01-02 | Baidu Usa Llc | Lane-attention: predicting vehicles' moving trajectories by learning their attention over lanes |
| RU2744012C1 (ru) * | 2019-12-24 | 2021-03-02 | Общество с ограниченной ответственностью "Яндекс Беспилотные Технологии" | Способы и системы для автоматизированного определения присутствия объектов |
| EP3943968A1 (en) * | 2020-07-24 | 2022-01-26 | Aptiv Technologies Limited | Methods and system for detection of objects in a vicinity of a vehicle |
| US12299542B2 (en) * | 2020-07-24 | 2025-05-13 | Actimize Ltd. | Systems and methods for unsupervised feature selection for online machine learning |
| US11835958B2 (en) * | 2020-07-28 | 2023-12-05 | Huawei Technologies Co., Ltd. | Predictive motion planning system and method |
| CA3126250A1 (en) * | 2020-07-29 | 2022-01-29 | Uatc, Llc | Recovering and simulating pedestrians in the wild |
| CN113095205B (zh) * | 2021-04-07 | 2022-07-12 | 北京航空航天大学 | 一种基于改进霍夫投票的点云目标检测方法 |
| DE102021203492B3 (de) * | 2021-04-08 | 2022-05-12 | Zf Friedrichshafen Ag | Computerimplementiertes Verfahren und System zum Trainieren eines maschinellen Lernverfahrens |
| US20230003871A1 (en) * | 2021-06-30 | 2023-01-05 | Zoox, Inc. | Associating radar data with tracked objects |
| CN113792637B (zh) * | 2021-09-07 | 2023-10-03 | 浙江大学 | 一种基于激光点云的目标车辆位置速度估计方法 |
| CN115965684A (zh) * | 2021-10-12 | 2023-04-14 | 奥林巴斯株式会社 | 医学成像系统及其操作方法、模拟器官的三维模型的局部变形的方法 |
| CN113971673B (zh) * | 2021-10-29 | 2026-02-06 | 北京经纬恒润科技股份有限公司 | 一种点云分割方法及装置 |
| EP4194885B1 (en) | 2021-12-09 | 2025-10-15 | Aptiv Technologies AG | Method for determining the mobility status of a target object |
| US12510656B2 (en) * | 2021-12-22 | 2025-12-30 | Intel Corporation | Apparatus, system, and method of processing point cloud radar information |
| US20230341545A1 (en) * | 2022-04-26 | 2023-10-26 | GM Cruise Holdings LLC. | Near field radar beamforming |
| US12221115B1 (en) | 2022-04-29 | 2025-02-11 | Zoox, Inc. | Self-supervised global velocity determination for perception system |
| DE102022121868A1 (de) * | 2022-08-30 | 2024-02-29 | Bayerische Motoren Werke Aktiengesellschaft | Verfahren und Assistenzeinrichtung zum Klassifizieren von Sensordetektionen basierend auf Punktwolken und entsprechend eingerichtetes Kraftfahrzeug |
| CN115150439B (zh) * | 2022-09-02 | 2023-01-24 | 北京电科智芯科技有限公司 | 感知数据的解析方法、系统及存储介质、电子设备 |
| CN115690727B (zh) * | 2022-09-14 | 2025-09-09 | 北京罗克维尔斯科技有限公司 | 骑行人跟踪方法、装置、设备、存储介质及车辆 |
| CN115923847B (zh) * | 2023-03-15 | 2023-06-02 | 安徽蔚来智驾科技有限公司 | 自动驾驶车辆的感知信息的预处理方法、装置及车辆 |
| US12499003B2 (en) | 2024-01-10 | 2025-12-16 | Oracle International Corporation | Configurable circular buffer for streaming multivariate ML estimation |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2017156847A (ja) | 2016-02-29 | 2017-09-07 | セコム株式会社 | 物体検出装置 |
| US20170371348A1 (en) | 2017-09-07 | 2017-12-28 | GM Global Technology Operations LLC | Ground reference determination for autonomous vehicle operations |
| US20180046649A1 (en) | 2016-08-12 | 2018-02-15 | Aquifi, Inc. | Systems and methods for automatically generating metadata for media documents |
| CN109410321A (zh) | 2018-10-17 | 2019-03-01 | 大连理工大学 | 基于卷积神经网络的三维重建方法 |
| CN109906608A (zh) | 2016-11-01 | 2019-06-18 | 松下电器(美国)知识产权公司 | 显示方法以及显示装置 |
| US10330787B2 (en) | 2016-09-19 | 2019-06-25 | Nec Corporation | Advanced driver-assistance system |
| CN110222953A (zh) | 2018-12-29 | 2019-09-10 | 北京理工大学 | 一种基于深度学习的电能质量混合扰动分析方法 |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7652618B2 (en) | 2008-02-15 | 2010-01-26 | Deere & Company | Method and system for determining velocity by using variable or distinct sampling rates |
| US9858640B1 (en) * | 2015-07-15 | 2018-01-02 | Hrl Laboratories, Llc | Device and method for merging 3D point clouds from sparsely distributed viewpoints |
| US10452068B2 (en) * | 2016-10-17 | 2019-10-22 | Uber Technologies, Inc. | Neural network system for autonomous vehicle control |
| US20180349746A1 (en) * | 2017-05-31 | 2018-12-06 | Uber Technologies, Inc. | Top-View Lidar-Based Object Detection |
| US10175697B1 (en) * | 2017-12-21 | 2019-01-08 | Luminar Technologies, Inc. | Object identification and labeling tool for training autonomous vehicle controllers |
-
2019
- 2019-09-30 US US16/587,605 patent/US11520037B2/en active Active
-
2020
- 2020-09-21 JP JP2022519454A patent/JP7637674B2/ja active Active
- 2020-09-21 CN CN202080068434.9A patent/CN114502979A/zh active Pending
- 2020-09-21 EP EP20789308.2A patent/EP4038408B1/en active Active
- 2020-09-21 WO PCT/US2020/051777 patent/WO2021067056A1/en not_active Ceased
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2017156847A (ja) | 2016-02-29 | 2017-09-07 | セコム株式会社 | 物体検出装置 |
| US20180046649A1 (en) | 2016-08-12 | 2018-02-15 | Aquifi, Inc. | Systems and methods for automatically generating metadata for media documents |
| US10330787B2 (en) | 2016-09-19 | 2019-06-25 | Nec Corporation | Advanced driver-assistance system |
| CN109906608A (zh) | 2016-11-01 | 2019-06-18 | 松下电器(美国)知识产权公司 | 显示方法以及显示装置 |
| US20170371348A1 (en) | 2017-09-07 | 2017-12-28 | GM Global Technology Operations LLC | Ground reference determination for autonomous vehicle operations |
| CN109410321A (zh) | 2018-10-17 | 2019-03-01 | 大连理工大学 | 基于卷积神经网络的三维重建方法 |
| CN110222953A (zh) | 2018-12-29 | 2019-09-10 | 北京理工大学 | 一种基于深度学习的电能质量混合扰动分析方法 |
Also Published As
| Publication number | Publication date |
|---|---|
| EP4038408A1 (en) | 2022-08-10 |
| EP4038408B1 (en) | 2025-07-23 |
| CN114502979A (zh) | 2022-05-13 |
| JP2022549913A (ja) | 2022-11-29 |
| US20210096241A1 (en) | 2021-04-01 |
| WO2021067056A1 (en) | 2021-04-08 |
| US11520037B2 (en) | 2022-12-06 |
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