Analysis of double support phase of biped robot and multi-objective optimization using genetic algorithm and particle swarm optimization algorithm

Rajendra, Rega; Pratihar, Dilip Kumar

doi:10.1007/s12046-014-0327-5

Cited by 13 publications

(5 citation statements)

References 20 publications

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“…, , ]-meaning that the reference's boundary values are expressed by + r,d = ,0 and − r,d = , . Assuming the zeroed control error ( d = r,d ) and considering the periodic condition of the hybrid zero dynamics solution, ,0 is described in dependency 12 of the other parameters in . Specifically, setting − r,d = , in (84) yields…”

Section: Reference Of Generalized Momentummentioning

confidence: 99%

“…For example, controllers based on the zero moment point (ZMP) stability criterion treat the robot system as fully actuated since no relative motion is allowed between the stance leg foot and the ground [9,10]. This makes it straightforward to create walking patterns that mimic humans with a continuous DSP, which can even be applied in different scenarios [11][12][13]. As an extension, the contact wrench sum (CWS) criterion [14][15][16] has been proposed as a more promising concept for generating the motion of the fully actuated robots.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid Zero Dynamics Control for Bipedal Walking with a Non-Instantaneous Double Support Phase

Luo¹,

Dyck²,

Zirkel³

et al. 2023

Preprint

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The hybrid zero dynamics control concept for bipedal walking is extended to include a non-instantaneous double support phase. A symmetric robot that consists of five rigid body segments which are connected by four actuated revolute joints is considered. Periodic walking gaits with a constant average walking speed consists of alternating single (SSP) and double support phases (DSP). Hybrid zero dynamics control designs usually assume an instantaneous DSP, which is a severe limitation. The proposed controllers use continuous SSPs and DSPs. Transitions between both phases are modeled as instantaneous events, when the rear leg lifts off at the end of the DSP and the swing leg touches down at the end of the SSP. Due to the fact that the model during the DSP has more actuators (4) than degrees of freedom (3), the system is overactuated. In order to combine it with the underactuated SSP model and then formulate a periodic walking gait, we suggest three controller designs for different applications. One with the underactuated DSP, one with the fully actuated DSP, and one with the overactuated DSP. A numerical optimization is used to generate energy efficient gaits in an offline process. According to the optimization results, artificially creating an underactuated controller for the DSP results in the most efficient gaits. Adding control tasks utilizing the full actuation or overactuation during the DSP significantly improves the gait stability.

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Section: Reference Of Generalized Momentummentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Hybrid Zero Dynamics Control for Bipedal Walking with a Non-Instantaneous Double Support Phase

Luo¹,

Dyck²,

Zirkel³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…To adapt to real-world environments, bipedal robots should have human-like walking patterns [ 45 ]. The reproduction of a walking cycle for a walking robot is based on the generation of a step sequence [ 46 ]. Each step is composed of two successive phases: the single-support phase (SSP) and double-support phase (DSP) [ 47 ].…”

Section: Gait Planning For Humanoidsmentioning

confidence: 99%

Robust Walking for Humanoid Robot Based on Divergent Component of Motion

Zhang

Shan

et al. 2022

Micromachines

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In order to perform various complex tasks in place of humans, humanoid robots should walk robustly in the presence of interference. In the paper, an improved model predictive control (MPC) method based on the divergent components of motion (DCM) is proposed. Firstly, the humanoid robot model is simplified to a finite-sized foot-pendulum model. Then, the gait of the humanoid robot in the single-support phase (SSP) and double-support phase (DSP) is planned based on DCM. The center of mass (CoM) of the robot will converge to the DCM, which simplifies the feedback control process. Finally, an MPC controller incorporating an extended Kalman filter (EKF) is proposed to realize the tracking of the desired DCM trajectory. By adjusting the step duration, the controller can compensate for CoM trajectory errors caused by disturbances. Simulation results show that—compared with the traditional method—the method we propose achieves improvements in both disturbed walking and uneven-terrain walking.

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“…is the deep stairs and is step length of stairs. The position of constraints during walking on stairs by the polynomial the hip joint is shown as: (14) Where is the time step and is the period. The specification of hip trajectory during walking on stairs with the movement line parallel with the descending stair can be expressed as: Stability contraints during walking up the stair on several parts including hp and ankle.…”

Section: Hip Trajectories Generationmentioning

confidence: 99%

“…The robust system has been verified by the simulation of 12 DoF [13]. Gait planning for ascending and descending stairs of 7 DoF biped robot considers the power consumption and the balance of walking using GA and PSO algorithm [14]. Motion planner based on random algorithm is used to reach the sequence of footstep [15].…”

Section: Introductionmentioning

confidence: 99%

Implementation and Integration of Fuzzy Algorithms for Descending Stair of KMEI Humanoid Robot

Sari

Dewanto

Pramadihanto

2020

emitter

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Locomotion of humanoid robot depends on the mechanical characteristic of the robot. Walking on descending stairs with integrated control systems for the humanoid robot is proposed. The analysis of trajectory for descending stairs is calculated by the constrains of step length stair using fuzzy algorithm. The established humanoid robot on dynamically balance on this matter of zero moment point has been pretended to be consisting of single support phase and double support phase. Walking transition from single support phase to double support phase is needed for a smooth transition cycle. To accomplish the problem, integrated motion and controller are divided into two conditions: motion working on offline planning and controller working online walking gait generation. To solve the defect during locomotion of the humanoid robot, it is directly controlled by the fuzzy logic controller. This paper verified the simulation and the experiment for descending stair of KMEI humanoid robot.

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Analysis of double support phase of biped robot and multi-objective optimization using genetic algorithm and particle swarm optimization algorithm

Cited by 13 publications

References 20 publications

Hybrid Zero Dynamics Control for Bipedal Walking with a Non-Instantaneous Double Support Phase

Hybrid Zero Dynamics Control for Bipedal Walking with a Non-Instantaneous Double Support Phase

Robust Walking for Humanoid Robot Based on Divergent Component of Motion

Implementation and Integration of Fuzzy Algorithms for Descending Stair of KMEI Humanoid Robot

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