A brief review of affordance in robotic manipulation research

Natsuki Yamanobe, Weiwei Wan, Ixchel G. Ramirez-Alpizar, Damien Petit, Tokuo Tsuji, Shuichi Akizuki, Manabu Hashimoto, Kazuyuki Nagata, Kensuke Harada

    Research output: Contribution to journalArticlepeer-review

    32 Citations (Scopus)


    This paper presents a brief review of affordance research in robotics, with special concentrations on its applications in grasping and manipulation of objects. The concept of affordance could be a key to realize human-like advanced manipulation intelligence. First, we discuss the concept of affordance while associating with the applications in robotics. Then, we intensively explore the studies that utilize affordance for robotic manipulation applications, such as object recognition, grasping, and object manipulation including tool-use. They obtain and use affordance by several ways like learning from human, using simulation, and real-world execution. Moreover, we show our current work, which is a cloud database for advanced manipulation intelligence. The database accumulates various data related to manipulation task execution and will be an open platform to leverage various affordance techniques.

    Original languageEnglish
    Pages (from-to)1086-1101
    Number of pages16
    JournalAdvanced Robotics
    Issue number19-20
    Publication statusPublished - 2017 Oct 18


    • Affordance
    • grasping
    • manipulation

    ASJC Scopus subject areas

    • Control and Systems Engineering
    • Software
    • Human-Computer Interaction
    • Hardware and Architecture
    • Computer Science Applications


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