Biped robot balance control—Based on FRP feedback mechanism and ZMP

Author(s):  
Gang Wang
Author(s):  
Carlotta Mummolo ◽  
William Z. Peng ◽  
Carlos Gonzalez ◽  
Joo H. Kim

A novel theoretical framework for the identification of the balance stability regions of biped systems is implemented on a real robotic platform. With the proposed method, the balance stability capabilities of a biped robot are quantified by a balance stability region in the state space of center of mass (COM) position and velocity. The boundary of such a stability region provides a threshold between balanced and falling states for the robot by including all possible COM states that are balanced with respect to a specified feet/ground contact configuration. A COM state outside of the stability region boundary is the sufficient condition for a falling state, from which a change in the specified contact configuration is inevitable. By specifying various positions of the robot’s feet on the ground, the effects of different contact configurations on the robot’s balance stability capabilities are investigated. Experimental walking trajectories of the robot are analyzed in relationship with their respective stability boundaries, to study the robot balance control during various gait phases.


Author(s):  
Yeoun-Jae Kim ◽  
Joon-Yong Lee ◽  
Ju-Jang Lee

Purpose – This paper aims to present a step-exchange strategy for balance control of a walking biped robot when a lateral impact acts suddenly. A step-out strategy has been recently proposed for balance control when an unknown lateral force acts to a biped robot during walking. This step-out strategy causes a robot to absorb the impact kinetic energy and efficiently maintain balance without falling down. Nevertheless, it was found that the previous strategies have drawbacks that the two foots should always be on the ground (double-support mode) after being balanced and the authors think it is difficult to continue walking after being balanced. Unlike the existing balance strategies, the proposed step-exchange strategy is to not only maintain balance but also to lift one leg in the air (single-support mode) after being balanced so that it is easy for a biped robot to keep walking after being balanced. Design/methodology/approach – In the proposed step-exchange strategy, forward Newton–Euler equation, angular momentum and energy conservation equation were derived. Hill-climbing algorithm is utilized for numerically finding a solution. To verify the proposed strategy, a biped robot by Open Dynamics Engine was stimulated, and experiments with a real biped robot (LRH-1) were also conducted. Findings – The proposed step-exchange strategy enables a walking biped robot under a lateral impact to keep balance and to keep a single-support mode after exchanging a leg. It is helpful for a biped robot to continue walking without any stop. It is found that the proposed step-exchange strategy can be applicable for maintaining balance even if a biped robot is moving. Even though this proposal seems immature yet, it is the first attempt to exchange the supporting foot itself. This strategy is very straightforward and intuitive because humans are also likely to exchange their supporting foot onto the opposite side when an unexpected force is acting. Research limitations/implications – The proposed step-exchange strategy described in this paper can be applicable in the situation when the external force is applied in the +Y direction, the left leg is the swing leg and the right leg is the stance leg, or it can also be applicable in the situation when the external force is applied in −Y direction, the right leg is the swing leg and the left leg is the stance leg (Figure 2 for ±Y force direction). If an impact force acts to the side of the swing leg, the other step-exchange strategy is needed. The authors are studying this issue as a future work. Originality/value – The authors have originated the proposed step-exchange strategy for balance control of a walking biped robot under lateral impact. The strategy is genuine and superior in comparison with the state-of-the-art strategy because not only can a biped robot be balanced but it can also easily continue walking by using the step-exchange strategy.


Robotica ◽  
2014 ◽  
Vol 34 (7) ◽  
pp. 1495-1516
Author(s):  
Yeoun-Jae Kim ◽  
Joon-Yong Lee ◽  
Ju-Jang Lee

SUMMARYIn this paper, we propose and examine a force-resisting balance control strategy for a walking biped robot under the application of a sudden unknown, continuous force. We assume that the external force is acting on the pelvis of a walking biped robot and that the external force in the z-direction is negligible compared to the external forces in the x- and y-directions. The main control strategy involves moving the zero moment point (ZMP) of the walking robot to the center of the robot's sole resisting the externally applied force. This strategy is divided into three steps. The first step is to detect an abnormal situation in which an unknown continuous force is applied by examining the position of the ZMP. The second step is to move the ZMP of the robot to the center of the sole resisting the external force. The third step is to have the biped robot convert from single support phase (SSP) to double support phase (DSP) for an increased force-resisting capability. Computer simulations and experiments of the proposed methods are performed to benchmark the suggested control strategy.


Mechatronics ◽  
2018 ◽  
Vol 49 ◽  
pp. 56-66 ◽  
Author(s):  
Satoshi Ito ◽  
Shingo Nishio ◽  
Masaaki Ino ◽  
Ryosuke Morita ◽  
Kojiro Matsushita ◽  
...  
Keyword(s):  

2014 ◽  
Vol 111 (9) ◽  
pp. 1852-1864 ◽  
Author(s):  
Lorenz Assländer ◽  
Robert J. Peterka

Healthy humans control balance during stance by using an active feedback mechanism that generates corrective torque based on a combination of movement and orientation cues from visual, vestibular, and proprioceptive systems. Previous studies found that the contribution of each of these sensory systems changes depending on perturbations applied during stance and on environmental conditions. The process of adjusting the sensory contributions to balance control is referred to as sensory reweighting. To investigate the dynamics of reweighting for the sensory modalities of vision and proprioception, 14 healthy young subjects were exposed to six different combinations of continuous visual scene and platform tilt stimuli while sway responses were recorded. Stimuli consisted of two components: 1) a pseudorandom component whose amplitude periodically switched between low and high amplitudes and 2) a low-amplitude sinusoidal component whose amplitude remained constant throughout a trial. These two stimuli were mathematically independent of one another and, thus, permitted separate analyses of sway responses to the two components. For all six stimulus combinations, the sway responses to the constant-amplitude sine were influenced by the changing amplitude of the pseudorandom component in a manner consistent with sensory reweighting. Results show clear evidence of intra- and intermodality reweighting. Reweighting dynamics were asymmetric, with slower reweighting dynamics following a high-to-low transition in the pseudorandom stimulus amplitude compared with low-to-high amplitude shifts, and were also slower for inter- compared with intramodality reweighting.


2012 ◽  
Vol 09 (03) ◽  
pp. 1250018 ◽  
Author(s):  
JOÃO P. FERREIRA ◽  
MANUEL CRISÓSTOMO ◽  
A. PAULO COIMBRA

This paper introduces two new important issues to be considered in the design of the zero moment point (ZMP) trajectory of a biped robot. It was verified experimentally that in the human gait the ZMP trajectory moves along the foot in a way that it is shifted forward relative to its center. To take this into account a shift parameter is then proposed. It was also verified experimentally that in the human gait the ZMP trajectory amplitude depends on the swing time, reducing to zero for a static gait. It is then proposed a parameter to take into account this variation with the swing time of the gait. Six experiments were carried out for three different X ZMP trajectory references. In order to evaluate and compare the performance of the biped robot using the three X ZMP trajectory references two performance indexes are proposed. For the real-time balance control of this 8 link biped robot it was used an intelligent computing control technique, the Support Vector Regression (SVR). The control method uses the ZMP error and its variation as inputs and the output is the correction of the robot's ankle and torso angles, necessary for the sagittal balance of the biped robot.


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