Pre-touch sensing for sequential manipulation

Yang, Boling; Lancaster, Patrick; Smith, Joshua R.

doi:10.1109/icra.2017.7989594

Cited by 31 publications

(22 citation statements)

References 19 publications

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“…Peak-to-peak distance error is 31.0 μm at the maximum. On the other hand, the peak-to-peak error of a commercially available TOF sensor is 4 mm(±2 mm) [7]. The peak-to-peak error of our sensor is less than 1/129-th of a commercially available sensor.…”

Section: A Distance Detectionmentioning

confidence: 66%

“…On the other hand, sequential manipulations have been realized by mounting optical time-of-flight (TOF) sensors on a gripper of a PR2 robot [7]. A low-cost ultra-tiny TOF sensor was also developed [8].…”

Section: A Sensor Requirementsmentioning

confidence: 99%

“…Here, A is the coefficient of cos ωt and B is the coefficient of sin ωt in the tilt mode. Therefore the phase φ(δ, d) in the tilt mode is given by equation (7).…”

Section: Tilt Modementioning

confidence: 99%

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High-Speed High-Precision Proximity Sensor for Detection of Tilt, Distance, and Contact

Koyama

Shimojo

Senoo

et al. 2018

IEEE Robot. Autom. Lett.

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We developed a fingertip-size proximity sensor that detects the distance to and the tilt angle of the surface of an object with the peak-to-peak distance error less than 1/129th (<31 µm) and the measuring time less than 1/10th (<1 ms) those of existing sensors. In addition, we realized the task of catching a fragile object (paper balloon) with a high-speed robot hand equipped with the sensor. High-speed, high-precision sensing enables contact detection independently of the contact force. We describe a robust contact detection method that does not depend on the reflectance, the tilt angle, or the shape of target objects surface. In experiments, we confirmed that the sensor could measure a distance of 2.85-20 mm (resolution: 44 µm in <3 mm) and a tilt angle of ±45 • (error: 1.47 • ) for objects with reflectances of 18% and 90%. We demonstrated that the hand could catch the paper balloon when dropped from a height of about 20 cm without crushing it.

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Section: A Distance Detectionmentioning

confidence: 66%

Section: A Sensor Requirementsmentioning

confidence: 99%

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High-Speed High-Precision Proximity Sensor for Detection of Tilt, Distance, and Contact

Koyama

Shimojo

Senoo

et al. 2018

IEEE Robot. Autom. Lett.

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“…Balek and Kelley [15] provide one of the earliest studies on how optical sensors can be integrated into robot grippers for obstacle avoidance, localization, and object recognition. More recent studies of optical based sensors have explored their application to grasping [16] [17] [18], sensor fusion [19] [20] [21], slip detection [22], and sequential manipulation [23]. Compared to other sensing modalities, optical sensors typically provide more accurate measurements over a wider range.…”

Section: Related Workmentioning

confidence: 99%

Improved Proximity, Contact, and Force Sensing via Optimization of Elastomer-Air Interface Geometry

Lancaster

Smith

Srinivasa

2019

2019 International Conference on Robotics and Automation (ICRA)

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We describe a single fingertip-mounted sensing system for robot manipulation that provides proximity (pre-touch), contact detection (touch), and force sensing (post-touch). The sensor system consists of optical time-of-flight range measurement modules covered in a clear elastomer. Because the elastomer is clear, the sensor can detect and range nearby objects, as well as measure deformations caused by objects that are in contact with the sensor and thereby estimate the applied force. We examine how this sensor design can be improved with respect to invariance to object reflectivity, signal-to-noise ratio, and continuous operation when switching between the distance and force measurement regimes. By harnessing time-of-flight technology and optimizing the elastomer-air boundary to control the emitted light's path, we develop a sensor that is able to seamlessly transition between measuring distances of up to 50 mm and contact forces of up to 10 newtons. Furthermore, we provide all hardware design files and software sources, and offer thorough instructions on how to manufacture the sensor from inexpensive, commercially available components.

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“…More recent studies demonstrate the use of proximity information for pre-grasp alignment and reactive grasping, 22,23 for point-cloud construction of objects 24 and slip detection, 25 and for learning a sequential manipulation task. 26 However, many barriers remain for these sensors to be integrated into self-contained prosthetic hands including the digital communication systems, the multiplexing of multiple sensors, and the wiring of the sensors throughout the device. In particular, none of these proximity sensors can classify spatial position and angular orientation of forces, which ensures that sensory restoration can take place reliably and repeatedly even when the external forces are not centered and/or to the fingertip surface.…”

Section: Introductionmentioning

confidence: 99%

Multi-modal prosthetic fingertip sensor with proximity, contact, and force localization capabilities

Segil

Patel

Klingner

et al. 2019

Advances in Mechanical Engineering

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The lack of sensory feedback provided by prosthetic hands dramatically limits the utility of the device. Peripheral nerve interfaces are now able to produce stable somatosensory percepts for upper limb amputees. Sensors must be able to detect forces across the fingers of the prosthesis in a repeatable and reliable fashion. We solved this concern with a novel multi-modal tactile sensor which consists of an infrared proximity sensor and a barometric pressure sensor embedded in an elastomer layer with potential use in prosthetic devices. Signals from both sensors measure proximity (0-10 mm), contact (0 N), and force (0-50 N) and are combined to localize impact at five spatial locations and three angles of incidence. Here, we describe the sensor design, its characterization, and data analysis. We use Gaussian process regression to fuse the signals from both sensors to obtain calibrated force in Newton with an R 2 value of 0.99. We use supervised learning to localize probe position and direction with classification accuracies of 96% and 89%, respectively. The complementary nature of both sensors leads to several sensing modalities that no one sensor can provide on its own and the repeatable, reliable, and compact form of the sensor enables use in multi-functional prosthetic hands.

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Pre-touch sensing for sequential manipulation

Cited by 31 publications

References 19 publications

High-Speed High-Precision Proximity Sensor for Detection of Tilt, Distance, and Contact

High-Speed High-Precision Proximity Sensor for Detection of Tilt, Distance, and Contact

Improved Proximity, Contact, and Force Sensing via Optimization of Elastomer-Air Interface Geometry

Multi-modal prosthetic fingertip sensor with proximity, contact, and force localization capabilities

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