Efficient design parameter optimization for musculoskeletal bipedal robots combining simulated and hardware-in-the-loop experiments

The design and tuning of bio-inspired musculoskeletal bipedal robots with tendon driven series elastic actuation (TD-SEA) including biarticular structures is more complex than for conventional rigid bipedal robots. To achieve a desired dynamic motion goal additional hardware parameters (spring coefficients, rest lengths, lever arms) of both, the TD-SEAs and the biarticular structures, need to be adjusted. Furthermore, the biarticular structures add correlations over multiple joints which increase the complexity of tuning of these parameters. Parameter adaption and tuning is needed to fit active and passive dynamics of the actuators and the control system. For the considered class of musculoskeletal bipedal robots no fully satisfying systematic approach to efficiently tune all of these parameters has been demonstrated yet. Conventional approaches for tuning of hardware parameters in rigid robots are either simulation based or use a hardware-in-the-loop optimization. This paper presents a new approach to efficiently optimize these parameters, by combining the advantages of simulation-in-the-loop and hardware-in-the-loop optimizations. Grahical interpretation of suitable metrics, like resulting quality values, are used to interpret the simulation results in order to efficiently guide the hardware experiments. By carefully considering the simulation results and adjusting the sequence of robot experiments based on biomechanical insights, the required number of hardware experiments can be significantly reduced. This approach is applied to the musculoskeletal BioBiped2 robot where the hardware parameters of the elastic actuation of the Gastrocnemius and Soleus structures are optimized. A comparison with a state-of-the-art hardware-in-the-loop optimization method demonstrates the efficiency of the presented approach.