Human Machine Interface for controlling a robot using image processing

Gautam, Ambuj K.; Vasu, V.; Raju, U. S. N.

doi:10.1016/j.proeng.2014.12.252

Cited by 7 publications

(4 citation statements)

References 2 publications

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“…A further class of HMIs is aimed at tracking the motion of different body parts, such as the eyes [43,187,188], the upper and lower limbs [189], and the head [190][191][192], via different kinds of vision devices. Eye-tracking technologies are usually based on infrared (IR) illuminators pointed at the eyes.…”

Section: Image-based Body Motion Hmismentioning

confidence: 99%

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Biosignal-Based Human–Machine Interfaces for Assistance and Rehabilitation: A Survey

Esposito

Centracchio

Andreozzi

et al. 2021

Sensors

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As a definition, Human–Machine Interface (HMI) enables a person to interact with a device. Starting from elementary equipment, the recent development of novel techniques and unobtrusive devices for biosignals monitoring paved the way for a new class of HMIs, which take such biosignals as inputs to control various applications. The current survey aims to review the large literature of the last two decades regarding biosignal-based HMIs for assistance and rehabilitation to outline state-of-the-art and identify emerging technologies and potential future research trends. PubMed and other databases were surveyed by using specific keywords. The found studies were further screened in three levels (title, abstract, full-text), and eventually, 144 journal papers and 37 conference papers were included. Four macrocategories were considered to classify the different biosignals used for HMI control: biopotential, muscle mechanical motion, body motion, and their combinations (hybrid systems). The HMIs were also classified according to their target application by considering six categories: prosthetic control, robotic control, virtual reality control, gesture recognition, communication, and smart environment control. An ever-growing number of publications has been observed over the last years. Most of the studies (about 67%) pertain to the assistive field, while 20% relate to rehabilitation and 13% to assistance and rehabilitation. A moderate increase can be observed in studies focusing on robotic control, prosthetic control, and gesture recognition in the last decade. In contrast, studies on the other targets experienced only a small increase. Biopotentials are no longer the leading control signals, and the use of muscle mechanical motion signals has experienced a considerable rise, especially in prosthetic control. Hybrid technologies are promising, as they could lead to higher performances. However, they also increase HMIs’ complexity, so their usefulness should be carefully evaluated for the specific application.

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Section: Image-based Body Motion Hmismentioning

confidence: 99%

“…A HMI based on head movement recognition has been presented by Gautam et al to control a small robotic car [192]. A camera captures the user's head images, which are processed to extract binary maps of face pixels.…”

Section: Image-based Body Motion Hmismentioning

confidence: 99%

Biosignal-Based Human–Machine Interfaces for Assistance and Rehabilitation: A Survey

Esposito

Centracchio

Andreozzi

et al. 2021

Sensors

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“…Since this review focuses on robotics, the term human-robot interface specifies the aforementioned term. Gautam et al describe a human-machine interface as "a technique, which is used for controlling machines with human activities" [2]. Within the context of robotics, Zhang gives a definition for HMI: "A human-machine interface in a robotic system is a terminal that allows the human operator to control, monitor, and collect data, and can also be used to program the system".…”

Section: Reflection Of Human-robot Interactionmentioning

confidence: 99%

“…Similar to the analysis for industrial robots, different human-robot interface strategies are described according to the modality, starting with gesture recognition. A range of other approaches exist, for example, guidance of an electric wheelchair using head movements [2]. Jones & Schmidlin conducted a thorough review of HRI for personal service robots to facilitate the design of usable personal service robots [30].…”

Section: Hri In Service Roboticsmentioning

confidence: 99%

Review of Interfaces for Industrial Human-Robot Interaction

Berg

2020

Curr Robot Rep

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Purpose of Review The review presents an overview of research approaches on human-robot interfaces in industrial and service robotics. Recent Findings Research approaches address especially speech and gesture recognition in both fields but are more explored in service robotics. However, the importance of interfaces in industrial robots increases. Summary The development of human-robot interfaces is leading towards intuitive interfaces, especially using speech and gesture recognition and combining them to multimodal interfaces.

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