인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
This study proposes a personalized velocity control system for an autonomous wheelchair by deriving human factors from the subjective opinions and requirements of users obtained through Human–Robot Interaction (HRI)–based usability evaluations. Using Bézier curve-based velocity profiles with different average deceleration levels, five deceleration modes are designed and tested with 38 participants in an indoor environment. The usability evaluation employs a seven-point Likert scale, and the collected responses are probabilistically analyzed to compute performance scores for each deceleration mode, leading to final performance indices defined as human factors. An optimal velocity profile that satisfies user requirements is generated based on these human factors, and a personalized control system is implemented by integrating a velocity controller with tracking error-based and feedforward compensation. In experiments with the same participants from the usability evaluation, the integrated controller closely tracks the optimal velocity profile, and the tracking error distribution is concentrated near zero, remaining within ±0.2 km/h. These results demonstrate that the proposed personalized control system improves driving safety and ride comfort while maintaining a high tracking performance by embedding quantified human factors into velocity planning and the integrated control framework.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-26-02-096088054
