{"title":"基于双信号比较接触检测的软手形状感知","authors":"Kai Shi, Jun Yu Li, Gang Bao","doi":"10.1108/ir-02-2023-0033","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe structural adaptive ability of the soft robot is fully demonstrated in the grasping task of the soft hand. A soft hand can easily realize the envelope operation of the object without planning. With the continuous development of robot applications, researchers are no longer satisfied with the ability of the soft hand to grasp. The purpose of this paper is to perceive the object’s shape while grasping to provide a decision-making basis for more intelligent robot applications.\n\n\nDesign/methodology/approach\nThis paper proposes a dual-signal comparison method to obtain the fingertip position. The dual signal includes the displacement calculated by the static model without considering the external load change and the displacement calculated by the bending sensor. The dual-signal comparison method can use the obvious change trend difference between the above two signals in the hover and contact states to identify the touch position. The authors make the soft hand scan around the object through touch operation to detect the object’s shape, and the tracks of every touch fingertip position can envelop the object’s shape.\n\n\nFindings\nThe experimental results show that the dual-signal comparison method can accurately identify the contact moment of soft fingers. This detection method makes the soft hand develop the shape detection ability. The soft hand in the experiment can perceive squares, circles and a few other complex shapes.\n\n\nOriginality/value\nThe dual-signal comparison method proposed in this paper can detect a touch action by using the signal change trend when the working condition suddenly changes with the rough robotic model and sensing, thus improving the utilization value of the measured signal. The problems of large model errors and inaccurate sensors also negatively impact the use of other soft robots. It is generally difficult to achieve good results by directly using these models and sensors with the thinking of rigid robot analysis. The dual-signal comparison method in this paper can provide some reference for this aspect.\n","PeriodicalId":54987,"journal":{"name":"Industrial Robot-The International Journal of Robotics Research and Application","volume":null,"pages":null},"PeriodicalIF":1.9000,"publicationDate":"2023-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Shape perception of soft hand based on dual-signal comparison contact detection\",\"authors\":\"Kai Shi, Jun Yu Li, Gang Bao\",\"doi\":\"10.1108/ir-02-2023-0033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe structural adaptive ability of the soft robot is fully demonstrated in the grasping task of the soft hand. A soft hand can easily realize the envelope operation of the object without planning. With the continuous development of robot applications, researchers are no longer satisfied with the ability of the soft hand to grasp. The purpose of this paper is to perceive the object’s shape while grasping to provide a decision-making basis for more intelligent robot applications.\\n\\n\\nDesign/methodology/approach\\nThis paper proposes a dual-signal comparison method to obtain the fingertip position. The dual signal includes the displacement calculated by the static model without considering the external load change and the displacement calculated by the bending sensor. The dual-signal comparison method can use the obvious change trend difference between the above two signals in the hover and contact states to identify the touch position. The authors make the soft hand scan around the object through touch operation to detect the object’s shape, and the tracks of every touch fingertip position can envelop the object’s shape.\\n\\n\\nFindings\\nThe experimental results show that the dual-signal comparison method can accurately identify the contact moment of soft fingers. This detection method makes the soft hand develop the shape detection ability. The soft hand in the experiment can perceive squares, circles and a few other complex shapes.\\n\\n\\nOriginality/value\\nThe dual-signal comparison method proposed in this paper can detect a touch action by using the signal change trend when the working condition suddenly changes with the rough robotic model and sensing, thus improving the utilization value of the measured signal. The problems of large model errors and inaccurate sensors also negatively impact the use of other soft robots. It is generally difficult to achieve good results by directly using these models and sensors with the thinking of rigid robot analysis. The dual-signal comparison method in this paper can provide some reference for this aspect.\\n\",\"PeriodicalId\":54987,\"journal\":{\"name\":\"Industrial Robot-The International Journal of Robotics Research and Application\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2023-07-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Industrial Robot-The International Journal of Robotics Research and Application\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1108/ir-02-2023-0033\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrial Robot-The International Journal of Robotics Research and Application","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1108/ir-02-2023-0033","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Shape perception of soft hand based on dual-signal comparison contact detection
Purpose
The structural adaptive ability of the soft robot is fully demonstrated in the grasping task of the soft hand. A soft hand can easily realize the envelope operation of the object without planning. With the continuous development of robot applications, researchers are no longer satisfied with the ability of the soft hand to grasp. The purpose of this paper is to perceive the object’s shape while grasping to provide a decision-making basis for more intelligent robot applications.
Design/methodology/approach
This paper proposes a dual-signal comparison method to obtain the fingertip position. The dual signal includes the displacement calculated by the static model without considering the external load change and the displacement calculated by the bending sensor. The dual-signal comparison method can use the obvious change trend difference between the above two signals in the hover and contact states to identify the touch position. The authors make the soft hand scan around the object through touch operation to detect the object’s shape, and the tracks of every touch fingertip position can envelop the object’s shape.
Findings
The experimental results show that the dual-signal comparison method can accurately identify the contact moment of soft fingers. This detection method makes the soft hand develop the shape detection ability. The soft hand in the experiment can perceive squares, circles and a few other complex shapes.
Originality/value
The dual-signal comparison method proposed in this paper can detect a touch action by using the signal change trend when the working condition suddenly changes with the rough robotic model and sensing, thus improving the utilization value of the measured signal. The problems of large model errors and inaccurate sensors also negatively impact the use of other soft robots. It is generally difficult to achieve good results by directly using these models and sensors with the thinking of rigid robot analysis. The dual-signal comparison method in this paper can provide some reference for this aspect.
期刊介绍:
Industrial Robot publishes peer reviewed research articles, technology reviews and specially commissioned case studies. Each issue includes high quality content covering all aspects of robotic technology, and reflecting the most interesting and strategically important research and development activities from around the world.
The journal’s policy of not publishing work that has only been tested in simulation means that only the very best and most practical research articles are included. This ensures that the material that is published has real relevance and value for commercial manufacturing and research organizations. Industrial Robot''s coverage includes, but is not restricted to:
Automatic assembly
Flexible manufacturing
Programming optimisation
Simulation and offline programming
Service robots
Autonomous robots
Swarm intelligence
Humanoid robots
Prosthetics and exoskeletons
Machine intelligence
Military robots
Underwater and aerial robots
Cooperative robots
Flexible grippers and tactile sensing
Robot vision
Teleoperation
Mobile robots
Search and rescue robots
Robot welding
Collision avoidance
Robotic machining
Surgical robots
Call for Papers 2020
AI for Autonomous Unmanned Systems
Agricultural Robot
Brain-Computer Interfaces for Human-Robot Interaction
Cooperative Robots
Robots for Environmental Monitoring
Rehabilitation Robots
Wearable Robotics/Exoskeletons.