PARLOMA – A Novel Human-Robot Interaction System for Deaf-Blind Remote Communication

Russo, Ludovico Orlando; Farulla, Giuseppe Airò; Pianu, Daniele; Salgarella, Alice Rita; Controzzi, Marco; Cipriani, Christian; Oddo, Calogero Maria; Geraci, Carlo; Rosa, Stefano; Indaco, Marco

doi:10.5772/60416

Cited by 25 publications

(38 citation statements)

References 46 publications

(49 reference statements)

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“…The achieved results show consistent improvements in sign reproduction (see Figure 3) with respect to [17]. As an example, the implemented adduction/abduction DoFs allow letters to be distinguished as V, U and R. Moreover, the hand is also able to reproduce handshapes that involve the wrist joint, such as letters H and P, which are impossible to reproduce with the hand in [17].…”

Section: Resultsmentioning

confidence: 55%

“…As in [17], we focus on the LIS alphabet without loss of generality. It has been proven that signs from many different SLs can be grouped similarly.…”

Section: Resultsmentioning

confidence: 99%

“…We used the same architecture of the experimental apparatus presented in [17]; we selected a subset of handshapes (from the LIS manual alphabet) and controlled the hand to reproduce them. Since this preliminary testing aimed to validate the ability of the hand in reproducing handshapes, we did not test the vision system.…”

Section: Resultsmentioning

confidence: 99%

“…where α is a parameter needed to minimize (17), λ ∈ 0 1 s.t. | d | ≤ Δ and Δ is the trust-region dimension.…”

Section: Trust-region Dogleg Methodsmentioning

confidence: 99%

“…Haptics can be a complementary communication means for HRI, in addition to vision and hearing. As an example, the PARLOMA [16,17] project has the ambitious goal of designing a low-cost remote communication system for deaf-blind people proficient in tactile SLs (tSLs). Deaf-blindness is a multi-sensorial impairment that deprives people of sight and hearing.…”

Section: Introductionmentioning

confidence: 99%

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A Low-Cost Open Source 3D-Printable Dexterous Anthropomorphic Robotic Hand with a Parallel Spherical Joint Wrist for Sign Languages Reproduction

Bulgarelli

Toscana

Russo

et al. 2016

International Journal of Advanced Robotic Systems

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We present a novel open-source 3D-printable dexterous anthropomorphic robotic hand specifically designed to reproduce Sign Languages' hand poses for deaf and deafblind users. We improved the InMoov hand, enhancing dexterity by adding abduction/adduction degrees of freedom of three fingers (thumb, index and middle fingers) and a three-degrees-of-freedom parallel spherical joint wrist. A systematic kinematic analysis is provided. The proposed robotic hand is validated in the framework of the PARLOMA project. PARLOMA aims at developing a telecommunication system for deaf-blind people, enabling remote transmission of signs from tactile Sign Languages. Both hardware and software are provided online to promote further improvements from the community.

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Section: Resultsmentioning

confidence: 55%

“…As in [17], we focus on the LIS alphabet without loss of generality. It has been proven that signs from many different SLs can be grouped similarly.…”

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

“…where α is a parameter needed to minimize (17), λ ∈ 0 1 s.t. | d | ≤ Δ and Δ is the trust-region dimension.…”

Section: Trust-region Dogleg Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A Low-Cost Open Source 3D-Printable Dexterous Anthropomorphic Robotic Hand with a Parallel Spherical Joint Wrist for Sign Languages Reproduction

Bulgarelli

Toscana

Russo

et al. 2016

International Journal of Advanced Robotic Systems

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Smart Tactile Gloves for Haptic Interaction, Communication, and Rehabilitation

Ozioko

Dahiya

2021

Advanced Intelligent Systems

134

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Smart wearable technologies are rapidly revolutionizing our interactive experience with the real and virtual world through a variety of virtual and augmented reality (VR/AR) systems [1,2] as well as underpinning advances in several technological areas touching life, such as healthcare technologies, [3,4] assistive technologies, [5][6][7] smart homes, [8] and robotics. [9][10][11] With the remarkable progress in related underpinning technologies such as 5G/6G communication, [12] the Internet of things (IoT), [13] tactile Internet, [14] machine learning, [15] and neural computing, [16] one can only see bright prospects for smart wearable technologies such as intelligent human machine interfaces (HMIs). [17] The HMI is at the center of efficient collaboration between humans and the rapidly advancing digitalized world. [18,19] Although human interaction with the real or virtual world takes place through the five basic sensory modalities, the majority of HMI technologies rely on vision, audio, and touch-sensing modalities. The latter is the major modality when it comes to physical interaction. [2,20,21] However, sensory feedback alone is not enough as the two-way tactile communication from the contact point to the controlling unit (e.g., the brain in the case of humans) [10,22] is important for any effective interaction. To achieve two-way tactile communication, an interface that has the capability of sensing a stimulus and receiving feedback is desired. For example, with interactive VR/AR systems, the user can send information via touch sensors and receive signals via different modalities, including visual, auditory, haptic, vestibular, and olfactory stimuli. VR tools that use computer-based interactive simulations to enable users to engage in environments that appear and feel similar to the real world are considered to be considerably useful for rehabilitation. [23,24] Likewise, the AR systems can infuse interactive virtual elements into the physical environment and thus supplement the real world. [23] The quality of the user experience with these systems depends on the intuitive interface offered by these systems, and their ability to provide easy-to-understand information. However, most VR/AR systems primarily provide visual and auditory feedback, which does not provide verisimilar immersive experiences. This is particularly unsuitable for people with impaired senses, such as the deaf and blind. [25] Conventionally, the HMI has involved gadgets such as keyboards, joysticks, mouses, screens, and Braille. However, the majority of these gadgets have one of more drawbacks, such as being bulky and nonintuitive, having low precision for monitoring human motions or transmitting complex commands, and having no capability to generate a feedback signal based on tactile sensing. As the requirement for richer, more versatile, and seamless interactions rises, researchers have explored several wearable options with sensors based on various sensing mechanisms such as capacitive, [9,[26][27][28][29]

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