Gesture-based Intention Prediction for Automatic Door Opening using Low-Resolution Thermal Sensors: A U-Net-based Deep Learning Approach

Chiu, Sheng-Ya; Chiu, Sheng-Yang; Tu, Yu-Ju; Hsu, C. S.

doi:10.1109/ecice52819.2021.9645718

Cited by 3 publications

(2 citation statements)

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“…In another study, Chiu et al (2021) proposed a design for recognizing human intention to open automatic doors by detecting and interpreting hand gestures. The proposed system aims to address privacy concerns and reduce the spread of infection during pandemics by enabling non-contact intention recognition.…”

Section: Resultsmentioning

confidence: 99%

“…When analyzing the data extracted from the literature and presented in Table 2 , it becomes clear that the most popular sensor used in designs is the RGB camera ( Fang et al, 2017 ; Li et al, 2018 ; Gardner et al, 2020 ; Jaouedi et al, 2020 ; Mohammadi Amin et al, 2020 ; Chiu et al, 2021 ; Ding and Zheng, 2022 ; Poulose et al, 2022 ; Tsitos et al, 2022 ; Zhang et al, 2022 ). This is likely due to the widespread use of image recognition applications in recent years, as well as the relative affordability and accessibility of RGB cameras in work environments.…”

Section: Discussionmentioning

confidence: 99%

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Integrating intention-based systems in human-robot interaction: a scoping review of sensors, algorithms, and trust

Zhang,

Doyle

2023

Front. Robot. AI

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The increasing adoption of robot systems in industrial settings and teaming with humans have led to a growing interest in human-robot interaction (HRI) research. While many robots use sensors to avoid harming humans, they cannot elaborate on human actions or intentions, making them passive reactors rather than interactive collaborators. Intention-based systems can determine human motives and predict future movements, but their closer interaction with humans raises concerns about trust. This scoping review provides an overview of sensors, algorithms, and examines the trust aspect of intention-based systems in HRI scenarios. We searched MEDLINE, Embase, and IEEE Xplore databases to identify studies related to the forementioned topics of intention-based systems in HRI. Results from each study were summarized and categorized according to different intention types, representing various designs. The literature shows a range of sensors and algorithms used to identify intentions, each with their own advantages and disadvantages in different scenarios. However, trust of intention-based systems is not well studied. Although some research in AI and robotics can be applied to intention-based systems, their unique characteristics warrant further study to maximize collaboration performance. This review highlights the need for more research on the trust aspects of intention-based systems to better understand and optimize their role in human-robot interactions, at the same time establishes a foundation for future research in sensor and algorithm designs for intention-based systems.

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Section: Resultsmentioning

confidence: 99%