{'fraction_non_alphanumeric': 0.015822784810126583, 'fraction_numerical': 0.0023734177215189874, 'mean_word_length': 4.883720930232558, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A fuzzy system for gait adaptation of biped walking robots

Past three decades witnessed a growing interest in biped walking robots because of their advantageous use in the human environment. However, their control is challenging because of their many DOFs and nonlinearities in their dynamics. Offline trajectory generation and the so-called open loop walking is one of the control approaches in the literature. There are various problems involved in this approach, the most pronounced one being the difficulty in tuning the gait parameters. This paper proposes an online fuzzy adaptation scheme for one of the trajectory parameters in the offline generated walking pattern. A fuzzy logic system, represented as a three-layer feed-forward neural network is employed to compute the parameter as a function of time. Fuzzy system parameters are adapted via backpropagation. An on-line tuning algorithm is employed. Virtual torsional springs are attached to the trunk center of the biped. The torques generated by the springs serve as the criteria for the tuning and they help maintaining a stable and a longer walk which is necessary for the on-line tuning process. 3D simulation techniques are employed for a 12-DOF biped robot to test the proposed adaptive method.