Journal of Robotics and Mechatronics
Online ISSN : 1883-8049
Print ISSN : 0915-3942
ISSN-L : 0915-3942
Special Issue on Systems Science of Hyper-Adaptability
Grid-Based Estimation of Transformation Between Partial Relationships Using a Genetic Algorithm
Sota NakamuraYuichi KobayashiTaisei Matsuura
ジャーナル オープンアクセス

2022 年 34 巻 4 号 p. 786-794


Human motor learning is characterized by adaptation, wherein information obtained in the past is transferred to a different situation. In this study, we investigate a grid-based computation for explaining the reuse of the information of an existing controller for adaptation to a partial malfunction of a controller. To this end, a motor learning scheme is adopted based on the detection and estimation of partial relationships. The transformation between the partial relationships is estimated based on a grid-based estimation of the two coordinate systems. In this estimation, the coordinate systems are optimized using a genetic algorithm. Two arms in a reflection are considered, and it is confirmed that the transformation of the differential kinematics (Jacobian), as an example of the partial relationships, can be estimated by the proposed method.



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