Control of walking robots based on manipulation of the zero 

moment point

Mitobe, Kazuhisa; Capi, Genci; Nasu, Yasuo

doi:10.1017/s0263574700002708

Cited by 106 publications

(50 citation statements)

References 5 publications

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“…The second approach considers the ZMP as an actuation signal. Using this principle, Sugihara (2009) and Mitobe et al (2000) manipulated the ZMP to control the reaction force acting on the COM for generating the bipedal gaits. In this method, the ZMP trajectory has a wide variety and doesn't necessarily stay in the foot center.…”

Section: Introductionmentioning

confidence: 99%

Walking pattern generation for a humanoid robot with compliant joints

Tsagarakis

Caldwell

2013

Auton Robot

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This work presents a walking pattern generator based on the control of the center of mass (COM) states and its experimental validations on the compliant humanoid robot COMAN powered by intrinsically compliant joints. To cope with the inaccuracies of the joint position tracking resulted by the physical compliance, the proposed pattern generator uses the feedback states of the COM and on-line computes the updated COM references. The position and velocity of the COM are the state variables, and the constrained ground reaction force (GRF) limited by the support polygon is the control effort to drive the real COM states to track the desired references. The frequency analysis of the COM demonstrates its low frequency spectrum that indicates the demand of a low control bandwidth which is suitable for a robot system with compliant joints. The effectiveness of the proposed gait generation method was demonstrated by the experiments performed on the COMAN robot. The experimental data such as the COM position and velocity tracking, the GRF applied on feet, the measured step length and the walking velocity are analyzed. The effect of the passive compliance is also discussed.

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Section: Introductionmentioning

confidence: 99%

Walking pattern generation for a humanoid robot with compliant joints

Tsagarakis

Caldwell

2013

Auton Robot

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“…For example, a very different class of tasks are such involving Physical Robotics [Pollack et al, 2000]. One physical task could be Control of Walking Robots, similar to the experiment presented in [Mitobe et al, 2000]. A Physical Robotics task would be a significantly more complex than the three executed in the context of this paper, as it requires the development of a more advanced controller with numerous additional sensors and actuators.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Controlling maximum evaluation duration in on-line and on-board evolutionary robotics

2014

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On-line evolution of robot controllers allows robots to adapt while they perform their proper tasks. In our investigations, robots contain their own self-sufficient evolutionary algorithm (known as the encapsulated approach) where individual solutions are evaluated by means of a time sharing scheme: an individual controller is given the run of the robot for some amount of time and fitness corresponds to the robot's task performance during that period.In this paper, we propose and provide a detailed analysis of two on-the-fly control schemes to set the evaluation time in highly dynamic scenarios with completely different tasks. One scheme, called the roulettewheel selection scheme, stochastically selects evaluation time from promising intervals similar to multiarmed bandit schemes. The other scheme, named HRule, tweaks the evaluation time using specific heuristics. Our experiments show that H-Rule gives stable performance in different scenarios and can serve as a viable alternative to pre-selected optimal evaluation time.

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“…An efficacy of a controller design scheme for a biped robot based on the center of mass (COM) [1][2][3][4][5][6] has been acknowledged. COM captures the core dynamics in the whole body motion, so that it enables an intuitive design of the controller with low computation cost.…”

Section: Introductionmentioning

confidence: 99%

“…A crucial issue in the scheme is the motion (position and velocity) estimation of COM, since it is embedded in a feedback loop and has a large influence to the controller performance. For example, some biped robot controllers [1][2][3][4][5][6] and on-line walking motion planners [7,8] that use the current position and velocity of COM have been proposed. COM is a point defined from the mass distribution and the whole-body configuration of the robot, and cannot be directly measured.…”

Section: Introductionmentioning

confidence: 99%

COM motion estimation of a biped robot based on kinodynamics and torque equilibrium

Masuya

Sugihara

2016

Advanced Robotics

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A novel technique to estimate motion of the center of mass (COM) for a biped robot is proposed. A Kalman filter is synthesized where the time evolution of COM is predicted from the external force and corrected based on kinematic estimation and torque equilibrium. They complementarily work to compensate the initial estimation offset, the error accumulation, and errors in modeled mass properties. It makes use of the authors' previous method to estimate the translational and rotational motion of the base body from inertial information and joint angle measurements. The information about torque equilibrium helps to reduce an uncertainty of the height of COM and to improve the estimation accuracy of it by utilizing an interference of the horizontal and vertical motion of COM. The parameters are tuned based on error analyses in mass properties and sensor signals. A comparative study showed a better performance of the proposed method than other methods through dynamics simulations. ARTICLE HISTORY

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Control of walking robots based on manipulation of the zero moment point

Cited by 106 publications

References 5 publications

Walking pattern generation for a humanoid robot with compliant joints

Walking pattern generation for a humanoid robot with compliant joints

Controlling maximum evaluation duration in on-line and on-board evolutionary robotics

COM motion estimation of a biped robot based on kinodynamics and torque equilibrium

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