Abstract:
This paper presents a novel method to identify a target object based on position and force data during motion demonstration. MCS is a system that copy and reproduce a ski...Show MoreMetadata
Abstract:
This paper presents a novel method to identify a target object based on position and force data during motion demonstration. MCS is a system that copy and reproduce a skillful human motion through bilateral teleoperation. Even though, MSC can teach a robot how to move, a robot cannot recognize a target object because conventional MCS does not record environmental information. In proposed system, a camera is used to add environmental information. We use object detection algorithm to detect not a target object but a robot itself. The detected robot area is used to combine manipulator's information in image space and in robotic work space. By checking detected robot area and haptic information, we can obtain a region around a target object automatically. After automatic target image data collection, we train Convolutional Auto Encoder(CAE) so that CAE can extract target information. The proposed neural network can selectively detect the target object for MCS, which means a robot understand a target for MCS. The results of end effectors' detection and target object extraction are shown in images through experiments.
Date of Conference: 14-16 September 2020
Date Added to IEEE Xplore: 10 November 2020
ISBN Information:
ISSN Information:
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- IEEE Keywords
- Index Terms
- Target Object ,
- Neural Network ,
- Imaging Data ,
- Object Detection ,
- Workspace ,
- Autoencoder ,
- Image Space ,
- End-effector ,
- Human Motion ,
- Information In Space ,
- Convolutional Autoencoder ,
- Image Data Collection ,
- Haptic Information ,
- Robot Workspace ,
- Bounding Box ,
- Reaction Force ,
- Image Recognition ,
- Joint Angles ,
- Jacobian Matrix ,
- Single Shot Multibox Detector ,
- Pixel Level ,
- Motion Data ,
- Motion Records ,
- Pixel Dimensions ,
- Position Tracking ,
- Force Control ,
- Masked Images ,
- Differential Modulation
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Target Object ,
- Neural Network ,
- Imaging Data ,
- Object Detection ,
- Workspace ,
- Autoencoder ,
- Image Space ,
- End-effector ,
- Human Motion ,
- Information In Space ,
- Convolutional Autoencoder ,
- Image Data Collection ,
- Haptic Information ,
- Robot Workspace ,
- Bounding Box ,
- Reaction Force ,
- Image Recognition ,
- Joint Angles ,
- Jacobian Matrix ,
- Single Shot Multibox Detector ,
- Pixel Level ,
- Motion Data ,
- Motion Records ,
- Pixel Dimensions ,
- Position Tracking ,
- Force Control ,
- Masked Images ,
- Differential Modulation
- Author Keywords