Studies show that the human nervous system is able to parameterize gait cycle phase using sensory feedback. In the field of bipedal robots, the concept of a phase variable has been successfully used to mimic this behavior by parameterizing the gait cycle in a time-independent manner. This approach has been applied to control a powered transfemoral prosthetic leg, but the proposed phase variable was limited to the stance period of the prosthesis only. In order to achieve a more robust controller, we attempt to find a new phase variable that fully parameterizes the gait cycle of a prosthetic leg. The angle with respect to a global reference frame at the hip is able to monotonically parameterize both the stance and swing periods of the gait cy...
The traditional view of motor control predicates that the central nervous system dictates the motion...
Theoretical studies and robotic experiments have shown that asymptotically stable periodic walking m...
© 2018 IEEE. In this paper we combine Gaussian process regression and impedance control, to illicit ...
Studies show that the human nervous system is able to parameterize gait cycle phase using sensory fe...
Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-depe...
Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-depe...
Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-depe...
Robotic studies have suggested a contribution of limit-cycle oscillation of the neuro-mechanical per...
Human locomotor activity (LA) recognition is important in the control of exoskeletons and prostheses...
The major problem with transfemoral prostheses is their capacity to compensate for the loss of the k...
In prior work, a minimal mathematical model of bipedal walking was developed to investigate the expe...
Humans and animals control their walking rhythms to maintain motion in a variable environment. The n...
In lower limb exoskeletons’ control scenario, synchronization between the delivered assistive torque...
We develop robust methods that allow specification, control, and transition of a multi-legged robot’...
Humans and animals control their walking rhythms to maintain motion in a variable environment. The n...
The traditional view of motor control predicates that the central nervous system dictates the motion...
Theoretical studies and robotic experiments have shown that asymptotically stable periodic walking m...
© 2018 IEEE. In this paper we combine Gaussian process regression and impedance control, to illicit ...
Studies show that the human nervous system is able to parameterize gait cycle phase using sensory fe...
Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-depe...
Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-depe...
Human locomotion is a rhythmic task in which patterns of muscle activity are modulated by state-depe...
Robotic studies have suggested a contribution of limit-cycle oscillation of the neuro-mechanical per...
Human locomotor activity (LA) recognition is important in the control of exoskeletons and prostheses...
The major problem with transfemoral prostheses is their capacity to compensate for the loss of the k...
In prior work, a minimal mathematical model of bipedal walking was developed to investigate the expe...
Humans and animals control their walking rhythms to maintain motion in a variable environment. The n...
In lower limb exoskeletons’ control scenario, synchronization between the delivered assistive torque...
We develop robust methods that allow specification, control, and transition of a multi-legged robot’...
Humans and animals control their walking rhythms to maintain motion in a variable environment. The n...
The traditional view of motor control predicates that the central nervous system dictates the motion...
Theoretical studies and robotic experiments have shown that asymptotically stable periodic walking m...
© 2018 IEEE. In this paper we combine Gaussian process regression and impedance control, to illicit ...