Design and Development of a Novel Robotic Gripper for Automated Scaffolding Assembly

Follini, Camilla; Cheng, Alexander Liu; Latorre, Galoget; Amores, Luis Freire

doi:10.1109/etcm.2018.8580276

Cited by 5 publications

(10 citation statements)

References 16 publications

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“…The mechanical consists of the physical parts that instantiate the reconfiguration modes particular to each user-type. Each of the computational mechanisms inherits and/or builds upon previous developments via Application Programming Interfaces (APIs) by the authors (with respect to facial- [7], object- [8], and voice-recognition [9]). That is to say:…”

Section: Methodology and Implementationmentioning

confidence: 99%

Development of An Adaptive Staircase System Actuated by Facial-, Object-, and Voice-Recognition

Cheng

Cruz

Guachamin

et al. 2019

2019 IEEE International Conference on E-Health Networking, Application &Amp; Services (HealthCom)

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This paper details a proof-of-concept development of an adaptive staircase system-type capable of user-specific mechanical reconfigurations actuated by facial-, object-, and voice-recognition. The system is described via two variationprototypes-developed at Technology Readiness Level 4-as instances of the same system-type. Accordingly, each prototype is informed by the same use-case considerations and requirements. Nevertheless, by means of their mechanical particulars, advantages and disadvantages specific to each variation are identified and explored. The present adaptive staircase system-type consists of two main components, one computational and the other mechanical. The computational component is built upon an inherited System Architecture previously developed and implemented by the authors. More specifically, the computational component uses Google's TensorFlow for facial-recognition; BerryNet for multi-object detection; and VoiceIt for voice-recognition. These three cloudcompatible, -based, or -dependent recognition mechanisms are used to ascertain the identity three user-types: (1) a person without perceivable physical disabilities; (2) a person reliant on a walking-cane; and (3) a person on a wheelchair. With the exception of the first case, the computational component proceeds to actuate mechanical transformations pertinent to each variety of disabilities depending on which user-type is identified. The objective of this implementations is to present an intuitive and automated vertical mobility solution capable of supporting users with varying degrees of reduced mobility.

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Section: Methodology and Implementationmentioning

confidence: 99%

Development of An Adaptive Staircase System Actuated by Facial-, Object-, and Voice-Recognition

Cheng

Cruz

Guachamin

et al. 2019

2019 IEEE International Conference on E-Health Networking, Application &Amp; Services (HealthCom)

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“…For example, further work is being conducted to integrate previously developed Object and Facial-Identity and -Expression Recognition mechanisms [5] based on TensorFlow™ [9] and Google Cloud Platform ® 's Cloud Vision API [10] with the Smart Sleeve's functionality. Further work is presently being undertaken to connect the Smart Sleeve mechanism with a robotic arm and gripper developed in parallel by the authors [11]. This robotic arm would be integrated into the intelligent built-environment in order to enhance a user's reach.…”

Section: Methodology and Implementationmentioning

confidence: 99%

Development of a Smart Sleeve Control Mechanism for Active Assisted Living

Cheng

Santos

et al. 2019

2019 IEEE 5th World Forum on Internet of Things (WF-IoT)

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This paper describes the development of a Smart Sleeve control mechanism for Active Assisted Living. The Smart Sleeve is a physically worn sleeve that extends the user's control capability within his/her intelligent built-environment by enabling (1) direct actuation and/or (2) teleoperation via a virtual interface. With respect to the first, the user may point his/her sleeve-wearing arm towards a door or a window and actuate an opening or a shutting; or towards a light and effect its turning on and off as well as regulating its intensity; or even towards a particular region to initiate ventilation of it. With respect to the second, the user may engage actuations in systems beyond his/her field of vision by interacting with a virtual representation of the intelligent built-environment projected on any screen or surface. For example, the user is able to shut the kitchen's door from his/her bedroom by extending the Smart Sleeve towards the door of a virtual representation of the kitchen projected (via a standard projector and/or television monitor) on the bedroom's wall. In both cases, the Smart Sleeve recognizes the object which the user wishes to engage withwhether in the real or the virtual worlds-(a) by detecting the orientation of the extended arm via an Accelerometer / Gyroscope / Magnetometer sensor; and (b) by detecting a specific forearm muscle contraction via Electromyography caused by the closing and opening of the fist, which serves to select the object. Once the object is identified and selected with said muscle contraction, subsequent arm gestures effect a variety of possible actuations for a given object (e.g., a window may be opened / shut or dragged to differing degrees or aperture; a light's intensity may be increased or decreased, etc.). In cases of ambiguous selections, the user my use voicecommands to explicitly identify the desired object of selection. Furthermore, due to this voice-based recognition mechanism, which recognizes both spoken commands as well the identity of the speakers, different rights to actuation may be assigned to different users. The Smart Sleeve is yet another mechanism integrated into an on-going development of a highly intuitive Active and Assisted Living implementation and its features, ones explicitly designed to enhance user-experience as well as to promote user well-being via intuitive interactions between human and non-human agents within the intelligent builtenvironment.

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“…146 5. 16 Pointing and selecting (Top), decreasing intensity (Middle, gesture left), and increasing intensity (Bottom, gesture right) of central illumination device. 147 5.17 Top: cluster of three nodes.…”

Section: Alex Quito November 2023mentioning

confidence: 99%

The Intelligent Built-Environment as Cyber-Physical System

Liu Cheng

2024

Architecture and the Built Environment

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This thesis presents an alternative approach to intelligence in the built-environment, departing from the two established yet divergent branches in the discourse: the Technical, centered around Information and Communication Technologies (ICTs), and represented by Ambient Intelligence (AmI) and Ambient Assisted Living (AAL); and the Architectural, centered around architectural / spatial experiences and considerations, and represented by Interactive Architecture and Adaptive Architecture. The promise of both AmI/AAL and IA/AA is constrained by rigid and increasingly outdated assumptions in their approaches—i.e., AmI’s / AAL’s approach to the built-environment, and IA’s / AA’s approach to ICTs. Moreover, it is impossible to combine them to yield a cohesive system due to disparity in their typical Technology Readiness Levels. That is, the sophistication of a system depends on that of its mutually complementing subsystems; and two or more subsystems may not mutually complement, sustain, and/or support one another if their levels of development do not correspond. Consequently, the presented alternative conceives the intelligent built-environment as a Cyber- Physical System. Under this approach, ICTs and Architectural considerations in conjunction instantiate intelligence fundamentally. The presented approach’s promise is illustrated via its application to a constrained use-case focused on the elderly. Twelve proof-of-concept demonstrators are developed based on key parameters pertaining to Indoor Environmental Quality and Quality of Life. While each demonstrator is presented as a discrete proof-of-concept, all build on the same core System Architecture and technological ecosystem, and are intended to be viewed as a collection of systems and services expressed within a same hypothetical environment.

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Design and Development of a Novel Robotic Gripper for Automated Scaffolding Assembly

Cited by 5 publications

References 16 publications

Development of An Adaptive Staircase System Actuated by Facial-, Object-, and Voice-Recognition

Development of An Adaptive Staircase System Actuated by Facial-, Object-, and Voice-Recognition

Development of a Smart Sleeve Control Mechanism for Active Assisted Living

The Intelligent Built-Environment as Cyber-Physical System

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