Integration of prioritized impedance controller in improved hierarchical operational-space torque control frameworks for legged locomotion robots

Lower-limb exoskeletons often use torque control to manipulate energy flow and ensure human safety. The accuracy of the applied torque greatly affects how well the motion is assisted and therefore improving it is always of interest. Feed-forward iterative learning, which is similar to predictive stride-wise integral control, has proven an effective compensation to feedback control for torque tracking in exoskeletons with complicated dynamics during human walking. Although the intention of iterative learning was initially to benefit average tracking performance over multiple strides, we found that, after proper gain tuning, it can also help improve real-time torque tracking. We used theoretical analysis to predict an optimal iterative-learning gain as the inverse of the passive actuator stiffness. Walking experiments resulted in an optimum gain equal to 0.99 ± 0.38 times the predicted value, confirming our hypothesis. The results of this study provide guidance for the design of torque controllers in robotic legged locomotion systems and will help improve the performance of robots that assist gait.

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Design and Construction of a New Version of the Epi.q UGV for Monitoring and Surveillance Tasks

Volume 4A: Dynamics, Vibration, and Control ◽

10.1115/imece2015-50163 ◽

2015 ◽

Cited By ~ 3

Author(s):

Giuseppe Quaglia ◽

Matteo Nisi

Keyword(s):

Mechanical Design ◽

Legged Locomotion ◽

Torque Control ◽

Sensing System ◽

Robot Architecture ◽

Robot Behavior ◽

Monitoring And Surveillance ◽

Definition Of ◽

Robot Configurations ◽

Design And Construction

The paper presents a new member of Epi.q robot family, a series of mobile robots with a wheel-legged locomotion and with the ability to overcome obstacles and move on uneven terrains. The particular feature of this robot family is the ability to switch from a wheel locomotion to a leg locomotion without any external active control but only depending on the dynamic conditions. In particular this work deals with the design of the latest prototype developed, analyzing the design and construction phases. This prototype is more powerful than the previous thanks to the possibility to have four driving units instead of two. The robot architecture has been studied in order to be modular. Several robot configurations can be obtained with the same structure and this allows to test how each component affect the overall robot behavior. Moreover the mechanical design is more accurate and reliable respect to previous versions. A sensing system has been introduced with the aim to evaluate the performances of each robot architecture. Finally an on-board processor has been added. This allows the definition of more complex control logics such as the cooperation between a speed control with a torque control in the four driving units configuration. Moreover it increases the smart tasks that the robot is able to perform such as the developing of a remote autonomous control rather than a manual drive by an operator.

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