Design Optimization of RML Glove for Improved Grasp Performance

Vanteddu, Teja; Sebastian, Bijo; Ben-Tzvi, Pinhas

doi:10.1115/dscc2018-9004

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…The linkage design is based on [15]'s optimization. The linkages force transformation ratio (R l ) is critical for calculating the fingertips' force.…”

Section: F Linkage Force Transformation Ratiomentioning

confidence: 99%

Data Driven Calibration and Control of Compact Lightweight Series Elastic Actuators for Robotic Exoskeleton Gloves

Guo

Pradhan

et al. 2021

IEEE Sensors J.

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The working principle of a SEA is based on using an elastic material connected serially to the mechanical power source to simulate the dynamic behavior of a human muscle. Due to weight and size limitations of a wearable robotic exoskeleton, the hardware design of the SEA is limited. Compact and lightweight SEAs usually have noisy signal output, and can easily be deformed. This paper uses a compact lightweight SEA designed for exoskeleton gloves to demonstrate immeasurable strain and friction force which can cause an average of 34.31% and maximum of 44.7% difference in force measurement on such SEAs. This paper proposes two data driven machine learning methods to accurately calibrate and control SEAs. The multi-layer perception (MLP) method can reduce the average force measurement error to 10.18% and maximum error to 29.13%. The surface fitting method (SF) method can reduce the average force measurement error to 8.06% and maximum error to 35.72%. In control experiments, the weighted MLP method achieves an average of 0.21N force control difference, and the SF method achieves an average of 0.29N force control difference on the finger tips of the exoskeleton glove.

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“…The linkage design is based on [15]'s optimization. The linkages force transformation ratio (R l ) is critical for calculating the fingertips' force.…”

Section: F Linkage Force Transformation Ratiomentioning

confidence: 99%

Data Driven Calibration and Control of Compact Lightweight Series Elastic Actuators for Robotic Exoskeleton Gloves

Guo

Pradhan

et al. 2021

IEEE Sensors J.

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“…According to statistical data published in 2010, over 6.7 million of U.S. adults have difficulty grasping or handling small objects [1]. To potentially better the lives of such a large group of people, a robotic exoskeleton glove is designed to be used as a rehabilitation device for Activities of Daily Living (ADL) [2]. This medical robotic exoskeleton glove is designed in the Robotics and Mechatronics Lab (RML) at Virginia Tech.…”

Section: Introductionmentioning

confidence: 99%

“…Chauhan, et al, proposed a grasp prediction algorithm to enhance the previous motion amplification system [14,15]. Vanteddu, el al, improved the structure of the glove [2] and added deformation control for more stable grasping [16].…”

Section: Introductionmentioning

confidence: 99%

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Personalized voice activated grasping system for a robotic exoskeleton glove

Guo

Pradhan

et al. 2022

Mechatronics

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Controlling an exoskeleton glove with a highly efficient human-machine interface (HMI), while accurately applying force to each joint remains a hot topic. This paper proposes a fast, secure, accurate, and portable solution to control an exoskeleton glove. This state of the art solution includes both hardware and software components. The exoskeleton glove uses a modified serial elastic actuator (SEA) to achieve accurate force sensing. A portable electronic system is designed based on the SEA to allow force measurement, force application, slip detection, cloud computing, and a power supply to provide over 2 hours of continuous usage. A voice-control-based HMI referred to as the integrated trigger-word configurable voice activation and speaker verification system (CVASV), is integrated into a robotic exoskeleton glove to perform high-level control. The CVASV HMI is designed for embedded systems with limited computing power to perform voice-activation and voice-verification simultaneously. The system uses MobileNet as the feature extractor to reduce computational cost. The HMI is tuned to allow better performance in grasping daily objects. This study focuses on applying the CVASV HMI to the exoskeleton glove to perform a stable grasp with force-control and slip-detection using SEA based exoskeleton glove. This research found that using MobileNet as the speaker verification neural network can increase the speed of processing while maintaining similar verification accuracy. I would also like to gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU.

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“…In observation of both the unaddressed design and control challenges, this work presents a step towards intelligent control of a linkage based exoskeleton for those with partial hand mobility using series elastic actuators (SEAs). A compact SEA design is presented and integrated with a linkage based finger mechanism that is an evolution of the mechanism first presented in [19] with optimized kinematics from [20]. The compliant elements in the SEA allow the user to be comfortably assisted by the device and express their intent.…”

Section: Introductionmentioning

confidence: 99%

A Series Elastic Actuator Design and Control in a Linkage Based Hand Exoskeleton

Chauhan

Ben-Tzvi

2019

Volume 3, Rapid Fire Interactive Presentations: Advances in Control Systems; Advances in Robotics and Mechatronics; Automotive

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This paper presents the design of a series elastic actuator and a higher level controller for said actuator to assist the motion of a user’s hand in a linkage based hand exoskeleton. While recent trends in the development of exoskeleton gloves has been to exploit the advantages of soft actuators, their size and power requirements limit their adoption. On the other hand, a series elastic actuator can provide compliant assistance to the wearer while remaining compact and lightweight. Furthermore, the linkage based mechanism integrated with the SEA offers repeatability and accuracy to the hand exoskeleton. By measuring the user’s motion intention through compression of the elastic elements in the actuator, a virtual dynamic system can be utilized that assists the users in performing the desired motion while ensuring the motion stability of the overall system. This work describes the detailed design of the actuator followed by performance tests using a simple PD controller on the integrated robotic exoskeleton prototype. The performance of the proposed high level controller is tested using the integrated exoskeleton glove mechanism for a single finger, using two types of input motion. Preliminary results are discussed as well as plans for integrating the proposed actuator and high level controller into a complete hand exoskeleton prototype to perform intelligent grasping.

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Design Optimization of RML Glove for Improved Grasp Performance

Cited by 5 publications

References 19 publications

Data Driven Calibration and Control of Compact Lightweight Series Elastic Actuators for Robotic Exoskeleton Gloves

Data Driven Calibration and Control of Compact Lightweight Series Elastic Actuators for Robotic Exoskeleton Gloves

Personalized voice activated grasping system for a robotic exoskeleton glove

A Series Elastic Actuator Design and Control in a Linkage Based Hand Exoskeleton

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