Abstract
A stable walking motion requires effective gait balancing and robust posture correction algorithms. However, to develop and implement such intelligent motion algorithms remains a challenging task for researchers. Effective sensory feedback for stable posture control is essential for bipedal locomotion. In order to minimize the modelling errors and disturbances, this paper presents an effective sensory system and an alternative approach in generating a stable Centre-of-Mass (CoM) trajectory by using an observer-based augmented model predictive control technique with sensory feedback. The proposed approach is used to apply an Augmented Model Predictive Control (AMPC) algorithm with an on-line time shift and to look ahead to process future data to optimize a control signal by minimizing the cost function so that the system is able to track the desired Zero Moment Point (ZMP) as closely as possible, and at the same time to limit the motion jerk. The robot's feet are fitted with force sensors to measure the contact force's location. An observer is also implemented into the system.
Highlights
The development of bipedal humanoid robots began more than 30 years ago
In order to compensate for this undesired effect, a new observer-based Augmented Model Predictive Control (AMPC) method is proposed in this paper
Together with the sensory feedback system, this method reduces the jerk produced by the ground landing impact forces and is able to improve the overall system performance of Zero Moment Point (ZMP) tracking under external disturbances
Summary
Despite numerous research efforts, controlling a bipedal robot is still an extremely challenging task in terms of adaptability, robustness and stability. The most common approaches are the Linear Inverted Pendulum Model (LIPM) and the Zero Moment Point (ZMP) method as in [1,2]. In order to compensate for this undesired effect, a new observer-based Augmented Model Predictive Control (AMPC) method is proposed in this paper. The effectiveness of the proposed scheme is demonstrated in a simulation and in comparison with the preview control method. Section three presents how the sensory system is deployed to enhance the effectiveness www.intechopen.com. A1n0d, 2X7ie7M:20in1g3: 1 The Design and Control of a Bipedal Robot with Sensory Feedback of the feedback system. Section five gives a detailed implementation of the proposed AMPC control approach. Section six concludes our proposed methods and recommends future work
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