Intelligent locomotion control on sloping surfaces
Information Sciences—Informatics and Computer Science: An International Journal
Soccer playing humanoid robots: Processing architecture, gait generation and vision system
Robotics and Autonomous Systems
Control of a Bipedal Walking Robot Using a Fuzzy Precompensator
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Biomimetic approach to tacit learning based on compound control
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Humanoid walking gait optimization using GA-Based neural network
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part II
Gait control for biped robot using fuzzy wavelet neural network
CIS'05 Proceedings of the 2005 international conference on Computational Intelligence and Security - Volume Part I
Intelligent fuzzy systems for aircraft landing control
FSKD'05 Proceedings of the Second international conference on Fuzzy Systems and Knowledge Discovery - Volume Part I
Gait synthesis based on FWN and PD controller for a five-link biped robot
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
Intelligent fuzzy q-learning control of humanoid robots
ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
Modelling and control of a walking four link robot
Mathematical and Computer Modelling: An International Journal
Balancing and posture controls for biped robots with unmodelled dynamics
ICIRA'12 Proceedings of the 5th international conference on Intelligent Robotics and Applications - Volume Part I
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In this paper, a learning scheme using a fuzzy controller to generate walking gaits is developed. The learning scheme uses a fuzzy controller combined with a linearized inverse biped model. The controller provides the control signals at each control time instant. The algorithm used to train the controller is “backpropagation through time”. The linearized inverse biped model provides the error signals for backpropagation through the controller at control time instants. Given prespecified constraints such as the step length, crossing clearance, and walking speed, the control scheme can generate the gait that satisfies these constraints. Simulation results are reported for a five-link biped robot