Optimization of Artificial Muscle Placements for a Humanoid Bipedal Robot

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Living Machines 2020: Biomimetic and Biohybrid Systems

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This work demonstrates an algorithm that is able to compute optimal placement for braided pneumatic actuators on a bipedal robot in order to emulate the biology of human legs. The algorithm calculates the torque that muscles are able to generate about a series of joints (back, hip, knee, ankle, subtalar, and metatarsophalangeal) in a human model. It then compares these torques to the torque that is achievable by a reduced number of pneumatic muscles actuating a bipedal robot model and optimizes the results to reduce the error between the robot and human model. The algorithm successfully finds new muscle placements that will be used in physical testing to verify that the torque output is correct and matches similarly to human capabilities. The algorithm was performed for three muscles about the back (lumbrosacral) joint: erector spinae, internal oblique, and external oblique. It generates placements capable of producing torque profiles that are more biologically realistic than the previously hand placed locations. Currently, the algorithm is not prevented from placing muscle paths that intersect the physical structure. This work will enable the development of controllable, physical models that more accurately capture force and torque capabilities of human muscles. Such physical models will enable more complete testing of how the nervous system performs effective control of over-actuated muscle systems, and if such systems have advantages for robotic applications.


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