&lt;title&gt;Spatially continuous six-degrees-of-freedom position and orientation sensor&lt;/title&gt;

Danisch, L.; Englehart, Kevin; Trivett, Andrew

doi:10.1117/12.339112

Cited by 11 publications

(3 citation statements)

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“…Such self-sensing input devices, usually not designed for motion capture, have been first demonstrated in the Gummi system [Schwesig et al 2004], which simulated a handheld, flexible display via two resistive pressure sensors. Other early work used the ShapeTape sensor [Danisch et al 1999] for input into a 3D modeling application [Balakrishnan et al 1999]. Metallic strain gauges embedded into flexible 3D printed 1D strips measure the bending and flexing of custom input devices [Chien et al 2015].…”

Section: Related Workmentioning

confidence: 99%

Deformation Capture via Soft and Stretchable Sensor Arrays

et al. 2019

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Fig. 1. Left to right: We propose a method for the fabrication of soft and stretchable silicone based capacitive sensor arrays. The sensor provides dense stretch measurements that, together with a data-driven prior, allow for the capture of surface deformations in real-time and without the need for line-of-sight.We propose a hardware and software pipeline to fabricate flexible wearable sensors and use them to capture deformations without line of sight. Our first contribution is a low-cost fabrication pipeline to embed multiple aligned conductive layers with complex geometries into silicone compounds. Overlapping conductive areas from separate layers form local capacitors that measure dense area changes. Contrary to existing fabrication methods, the proposed technique only requires hardware that is readily available in modern fablabs. While area measurements alone are not enough to reconstruct the full 3D deformation of a surface, they become sufficient when paired with a data-driven prior. A novel semi-automatic tracking algorithm, based on an elastic surface geometry deformation, allows to capture ground-truth data with an optical mocap system, even under heavy occlusions or partially unobservable markers. The resulting dataset is used to train a regressor based on deep neural networks, directly mapping the area readings to global positions of surface vertices. We demonstrate the flexibility and accuracy of the proposed hardware and software in a series of controlled experiments, and design a prototype of wearable wrist, elbow and biceps sensors, which do not require line-of-sight and can be worn below regular clothing.

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Section: Related Workmentioning

confidence: 99%

Deformation Capture via Soft and Stretchable Sensor Arrays

et al. 2019

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“…The visual systems which are also known as optical systems can either be marker-based or markerfree based. Above and beyond mechanical, inertial, acoustic 3 , magnetic, optical sensing 4 , innovative techniques such as conductive fibers 5 , inductive fiber mesh 6 , optical fiber loss 7 and piezo-resistive fabric 8 are introduced. Nevertheless, these new sensing methods still cannot achieve the response (200 Hz), accuracy (±1°), robustness and low cost required by most applications.…”

Section: Classification Of Motion Capture Systemsmentioning

confidence: 99%

Development of a wearable motion capture system using linear encoder

Goh¹

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Motion capture is gaining high popularity in recent years in the field of robotics, animation, health care, computer games, virtual reality, security, and entertainment. Through the use of advance motion tracking system, human motion data can be captured, processed and used in potential human-centered environment for the control of humanoid robots and medical assistive devices to perform complex and daunting task. However, the range of possible human motion consist of a very large number of degrees of freedom and the task of motion capturing, generation and control of these biomimetic systems can be very cumbersome and complicated. The challenge faced by modern researchers in the field of motion capture is that there is no single solution that can address the shortcomings faced by various commercial motion capture systems available and these systems are usually very expensive and are intricate in the setting up and application process. Hence, the focus of this project is on the development a novel yet cheap sensing technology with high performance un-tethered wearable human motion processing system that is used for real-time sensing and processing of anatomical motion data. Embedded sensing techniques for the detection of individual joint movement, ergonomics and placement of the sensing system addressing wearability issue and the performance of the sensors will be the main research topics. Major applications of this human motion capturing system will be in the instantaneous control and manipulation of virtual figures in a 3-D virtual environment such as interactive media, games and films, and also the control of articulated physical biomechatronic systems, such as humanoid robots and rehabilitation devices. In this project, a new type of sensors was developed to detect bending and warping of limbs and joints as the fundamental element of the body motion processing system. The sensing device is to be free from signal interference, obstruction or shadow effect, these sensor strips can be woven into a web directly worn by the human or embedded into the clothing. The patterns of the strip sensor web can be configured for a specific application as well as customized based on the biometric data of the user. An embedded processing unit will handle the bending information of all strip sensors to produce the complete body motion data based on the patterns of the strips and biometric data of the user in ATTENTION: The Singapore Copyright Act applies to the use of this document. Nanyang Technological University Library-II-real-time. The real-time motion data can be used for control and manipulation of physical and virtual systems through wireless communication capability built into the system.

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“…This variation affects the accuracy and reliability of the motion capture process. Therefore a scale factor (SF) is inserted into equation 3 (15) The scale factor is obtained through a calibrating process:…”

Section: Calibrationmentioning

confidence: 99%

Embedded and visual programming for SmartSuit motion capture system

Nguyen¹

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<title>Spatially continuous six-degrees-of-freedom position and orientation sensor</title>

Cited by 11 publications

References 0 publications

Deformation Capture via Soft and Stretchable Sensor Arrays

Deformation Capture via Soft and Stretchable Sensor Arrays

Development of a wearable motion capture system using linear encoder

Embedded and visual programming for SmartSuit motion capture system

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