A reach motion generation algorithm based on posture memories.

BACKGROUND: Most existing models/algorithms for simulating goal-directed human motions were designed to generate a single "realistic" motion for a given input scenario. OBJECTIVE: This study presents a novel reach motion generation algorithm utilizing multiple posture memories. The algorithm aims to...

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Publicado en:Work Vol. 65; no. 1; pp. 215 - 224
Autores principales: Yoo, Taekbeom, Park, Woojin
Formato: algorithm pictorial tables/charts Journal Article
Publicado: Sage Publications Inc. 2020
Acceso en línea:Ver este registro en EBSCOhost
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        atl: A reach motion generation algorithm based on posture memories.
      aug:
        au:
          Yoo, Taekbeom
          Park, Woojin
        affil: Department of Industrial Engineering, Seoul National University, Seoul, South Korea
      sug:
        subj:
          Motion Analysis Systems
          Computer Simulation
          Algorithms
          Posture
          Memory
          Time and Motion Studies
          Work Environment
          Ergonomics
          Models, Theoretical
          Kinematics
          Random Sample
          Mathematics
          Anthropometry
      ab: BACKGROUND: Most existing models/algorithms for simulating goal-directed human motions were designed to generate a single "realistic" motion for a given input scenario. OBJECTIVE: This study presents a novel reach motion generation algorithm utilizing multiple posture memories. The algorithm aims to compute and visualize a set of human reach motions that approximates the full range of physically and physiologically feasible human motions for a given input scenario. METHODS: The algorithm utilizes posture memories constructed specifically for an individual worker using a probabilistic posture generation and registration process. The posture memories relate a hand position to the set of postures that place the individual's hand in its vicinity. When given an input scenario, the algorithm first generates different hand paths connecting the starting and ending hand positions specified in the scenario. Then, for each hand path, the algorithm produces different "feasible" motions by selecting and connecting multiple postures stored in the posture memories; the postures corresponding to the hand positions along the hand path are utilized. CONCLUSIONS: The proposed algorithm helps understand the impacts of workplace design on the range of feasible human motion behaviors, and, thereby, contributes to the computer-aided ergonomics design of work tasks and workplaces.
      pubtype: Academic Journal
      doctype:
        algorithm
        pictorial
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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