Recently, numerous musculoskeletal robots have been developed to realize the flexibility and dexterity analogous to human beings\nand animals. However, because the arrangement of many actuators is complex, the design of the control system for the robot is\ndifficult and challenging. We believe that control methods inspired by living things are important in the development of the\ncontrol systems for musculoskeletal robots. In this study, we propose a muscle coordination control method using attractor\nselection, a biologically inspired search method, for an antagonistic-driven musculoskeletal robot in which various muscles\n(monoarticular muscles and a polyarticular muscle) are arranged asymmetrically. First, muscle coordination control models for\nthe musculoskeletal robot are built using virtual antagonistic muscle structures with a virtually symmetric muscle arrangement.\nNext, the attractor selection is applied to the control model and subsequently applied to the previous control model without\nmuscle coordination to compare the control modelâ??s performance. Finally, position control experiments are conducted, and the\neffectiveness of the proposed muscle coordination control and the virtual antagonistic muscle structure is evaluated.
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