The transfer of information between a human and a robot is of vital importance for robotic telemanipulation systems.In this paper,we propose a novel strategy-assisted shared control(SASC)scheme driven by electromyogra...The transfer of information between a human and a robot is of vital importance for robotic telemanipulation systems.In this paper,we propose a novel strategy-assisted shared control(SASC)scheme driven by electromyography(EMG)signals for robot telemanipulation.First,we develop an EMG decoding scheme to achieve reliable online performance,where ten features are extracted and selected and then classified by machine learning algorithms.Several feature selection methods are compared to learn a compact representation from original feature sets.Then,a vision-based module is designed for object detection and localization,which helps to grasp or release objects autonomously.Moreover,online visual feedback of environmental states and audio feedback of EMG decoding results are used for better perception of environmental contexts.A platform integrated with a robot arm,an RGB-D camera,and a pneumatic sucker,among others,is developed to evaluate the proposed method.The best accuracy of EMG recognition is 97.18%±10.61%,achieved by the support vector machine and features selected by recursive feature elimination.Two paradigms driven by a joystick or EMG are compared with SASC in a robotic telemanipulation task.The performance shows that SASC reaches a successful rate of 100% with the least time of 61.97±9.89 s.The completion times of SASC are only 67.78% and 55.71% of the two contrast methods,respectively.This shows that the proposed scheme has the potential to replace classical methods with reliable performance and less time,which provides a novel solution for this field of study.展开更多
Microrobots powered by an external magnetic field could be used for sophisticated medical applications such as cell treatment,micromanipulation,and noninvasive surgery inside the body.Untethered microrobot application...Microrobots powered by an external magnetic field could be used for sophisticated medical applications such as cell treatment,micromanipulation,and noninvasive surgery inside the body.Untethered microrobot applications can benefit from haptic technology and telecommunication,enabling telemedical micro-manipulation.Users can manipulate the microrobots with haptic feedback by interacting with the robot operating system remotely in such applications.Artificially created haptic forces based on wirelessly transmitted data and model-based guidance can aid human operators with haptic sensations while manipulating microrobots.The system presented here includes a haptic device and a magnetic tweezer system linked together using a network-based teleoperation method with motion models in fluids.The magnetic microrobots can be controlled remotely,and the haptic interactions with the remote environment can be felt in real time.A time-domain passivity controller is applied to overcome network delay and ensure stability of communication.This study develops and tests a motion model for microrobots and evaluates two image-based 3D tracking algorithms to improve tracking accuracy in various Newtonian fluids.Additionally,it demonstrates that microrobots can group together to transport multiple larger objects,move through microfluidic channels for detailed tasks,and use a novel method for disassembly,greatly expanding their range of use in microscale operations.Remote medical treatment in multiple locations,remote delivery of medication without the need for physical penetration of the skin,and remotely controlled cell manipulations are some of the possible uses of the proposed technology.展开更多
基金supported by the National Key Research and Development Program of China(Grant Nos.2022YFF1202500,2022YFF1202502,2022YFB4703200,2023YFB4704700,and 2023YFB4704702)the National Natural Science Foundation of China(Grant Nos.U22A2067,U20A20197,61773369,61903360,92048302,and 62203430)the China Postdoctoral Science Foundation(Grant No.2022M723312)。
文摘The transfer of information between a human and a robot is of vital importance for robotic telemanipulation systems.In this paper,we propose a novel strategy-assisted shared control(SASC)scheme driven by electromyography(EMG)signals for robot telemanipulation.First,we develop an EMG decoding scheme to achieve reliable online performance,where ten features are extracted and selected and then classified by machine learning algorithms.Several feature selection methods are compared to learn a compact representation from original feature sets.Then,a vision-based module is designed for object detection and localization,which helps to grasp or release objects autonomously.Moreover,online visual feedback of environmental states and audio feedback of EMG decoding results are used for better perception of environmental contexts.A platform integrated with a robot arm,an RGB-D camera,and a pneumatic sucker,among others,is developed to evaluate the proposed method.The best accuracy of EMG recognition is 97.18%±10.61%,achieved by the support vector machine and features selected by recursive feature elimination.Two paradigms driven by a joystick or EMG are compared with SASC in a robotic telemanipulation task.The performance shows that SASC reaches a successful rate of 100% with the least time of 61.97±9.89 s.The completion times of SASC are only 67.78% and 55.71% of the two contrast methods,respectively.This shows that the proposed scheme has the potential to replace classical methods with reliable performance and less time,which provides a novel solution for this field of study.
基金supported by National Science Foundation Grant No.2123824.
文摘Microrobots powered by an external magnetic field could be used for sophisticated medical applications such as cell treatment,micromanipulation,and noninvasive surgery inside the body.Untethered microrobot applications can benefit from haptic technology and telecommunication,enabling telemedical micro-manipulation.Users can manipulate the microrobots with haptic feedback by interacting with the robot operating system remotely in such applications.Artificially created haptic forces based on wirelessly transmitted data and model-based guidance can aid human operators with haptic sensations while manipulating microrobots.The system presented here includes a haptic device and a magnetic tweezer system linked together using a network-based teleoperation method with motion models in fluids.The magnetic microrobots can be controlled remotely,and the haptic interactions with the remote environment can be felt in real time.A time-domain passivity controller is applied to overcome network delay and ensure stability of communication.This study develops and tests a motion model for microrobots and evaluates two image-based 3D tracking algorithms to improve tracking accuracy in various Newtonian fluids.Additionally,it demonstrates that microrobots can group together to transport multiple larger objects,move through microfluidic channels for detailed tasks,and use a novel method for disassembly,greatly expanding their range of use in microscale operations.Remote medical treatment in multiple locations,remote delivery of medication without the need for physical penetration of the skin,and remotely controlled cell manipulations are some of the possible uses of the proposed technology.
