Gesture controlled robot

Lavanya, K N; Shree, D Ramya; Nischitha, B R; Asha, T; Gururaj, C.

doi:10.1109/iceeccot.2017.8284549

Cited by 11 publications

(3 citation statements)

References 2 publications

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“…The selected criteria were a subset of the list found in Section 1.1 of the literature review. These criteria were selected from the larger list to specifically adhere to the design approaches used in [ 3 , 4 ] which successfully produced enervative and effective solutions. The final set of governing criteria used in this project are listed below in order of importance: Reliability in issuing the intended command: This criterion graded both the number of unique commands the algorithms can issue, and the algorithm’s ability to distinguish between these unique commands.…”

Section: Methodsmentioning

confidence: 99%

“…Alternative-control algorithms consist of two main components, a non-standard human–computer interface (HCI) and a command mapping algorithm [ 1 , 2 , 3 , 4 ]. An alternative-control algorithm is considered successful in its application if the alternative HCI extends upon the functionality offered by the conventional control medium.…”

Section: Introductionmentioning

confidence: 99%

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Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition

Khaksar,

Checker,

Borazjan

et al. 2023

Sensors

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Gesture recognition is a mechanism by which a system recognizes an expressive and purposeful action made by a user’s body. Hand-gesture recognition (HGR) is a staple piece of gesture-recognition literature and has been keenly researched over the past 40 years. Over this time, HGR solutions have varied in medium, method, and application. Modern developments in the areas of machine perception have seen the rise of single-camera, skeletal model, hand-gesture identification algorithms, such as media pipe hands (MPH). This paper evaluates the applicability of these modern HGR algorithms within the context of alternative control. Specifically, this is achieved through the development of an HGR-based alternative-control system capable of controlling of a quad-rotor drone. The technical importance of this paper stems from the results produced during the novel and clinically sound evaluation of MPH, alongside the investigatory framework used to develop the final HGR algorithm. The evaluation of MPH highlighted the Z-axis instability of its modelling system which reduced the landmark accuracy of its output from 86.7% to 41.5%. The selection of an appropriate classifier complimented the computationally lightweight nature of MPH whilst compensating for its instability, achieving a classification accuracy of 96.25% for eight single-hand static gestures. The success of the developed HGR algorithm ensured that the proposed alternative-control system could facilitate intuitive, computationally inexpensive, and repeatable drone control without requiring specialised equipment.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition

Khaksar,

Checker,

Borazjan

et al. 2023

Sensors

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show abstract

“…Hence, gesture recognition has a huge application ranging from very simple applications to interact with home appliances such as the TV [4] to complex systems of telemedicine [5]. In addition, hand gesture recognition has a promising future in some circumstances where hands are not able to touch equipment, such as in medical environments [6], helping impaired people to communicate [7], game-based rehabilitation applications [8,9], cooking scenarios [10], controlled robots at industrial environments [11], vehicle interfaces [12,13], or military needs [14].…”

Section: Introductionmentioning

confidence: 99%

A Wearable Textile 3D Gesture Recognition Sensor Based on Screen-Printing Technology

Ferri

Llopis

Moreno

et al. 2019

Sensors

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Research has developed various solutions in order for computers to recognize hand gestures in the context of human machine interface (HMI). The design of a successful hand gesture recognition system must address functionality and usability. The gesture recognition market has evolved from touchpads to touchless sensors, which do not need direct contact. Their application in textiles ranges from the field of medical environments to smart home applications and the automotive industry. In this paper, a textile capacitive touchless sensor has been developed by using screen-printing technology. Two different designs were developed to obtain the best configuration, obtaining good results in both cases. Finally, as a real application, a complete solution of the sensor with wireless communications is presented to be used as an interface for a mobile phone.

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