Bio-Inspired Optimal Control Framework to Generate Walking Motions for the Humanoid Robot iCub Using Whole Body Models

Hu, Yue; Mombaur, Katja

doi:10.3390/app8020278

Cited by 15 publications

(9 citation statements)

References 43 publications

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“…Hu and Mombaur present an optimal control-based approach for the humanoid robot iCub that allows to generate optimized walking motions using a precise whole-body dynamic model of the robot. The optimal control problem is formulated to minimize a set of desired objective functions with respect to physical constraints of the robot and contact constraints of the walking phases [2]. Jiang et al propose a jumping control scheme for a bipedal robot to perform a high jump taking into account the motion during the launching phase.…”

Section: Biped Robotsmentioning

confidence: 99%

Special Feature on Bio-Inspired Robotics

2018

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Section: Biped Robotsmentioning

confidence: 99%

Special Feature on Bio-Inspired Robotics

2018

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“…Many biped robot algorithms have been developed, such as balance control and inverse kinematics [1][2][3]. The zero moment point (ZMP) and walking dynamics analysis can be adopted to enable a robot to walk steadily [4][5][6][7]. However, these methods require copious calculations; researchers must develop an approximate or simple dynamic model.…”

Section: Introductionmentioning

confidence: 99%

Real-Time FPGA-Based Balance Control Method for a Humanoid Robot Pushed by External Forces

et al. 2020

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In this paper, a real-time balance control method is designed and implemented on a field-programmable gate array (FPGA) chip for a small-sized humanoid robot. In the proposed balance control structure, there are four modules: (1) external force detection, (2) push recovery balance control, (3) trajectory planning, and (4) inverse kinematics. The proposed method is implemented on the FPGA chip so that it can quickly respond to keep the small-sized humanoid robot balanced when it is pushed by external forces. A gyroscope and an accelerometer are used to detect the inclination angle of the robot. When the robot is under the action of an external force, an excessively large inclination angle may be produced, causing it to lose its balance. A linear inverted pendulum with a flywheel model is employed to estimate a capture point where the robot should step to maintain its balance. In addition, the central pattern generators (CPGs) with a sinusoidal function are adopted to plan the stepping trajectories. Some experimental results are presented to illustrate that the proposed real-time balance control method can effectively enable the robot to keep its balance to avoid falling down.

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“…These methods have unique advantages and disadvantages. Recently, newer gait-planning methods [9][10][11][12][13] have been developed that do not rely on the ZMP and have indeed produced marked improvements in humanoid robot walking.…”

Section: Introductionmentioning

confidence: 99%

Turning Gait Planning Method for Humanoid Robots

et al. 2018

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The most important feature of this paper is to transform the complex motion of robot turning into a simple translational motion, thus simplifying the dynamic model. Compared with the method that generates a center of mass (COM) trajectory directly by the inverted pendulum model, this method is more precise. The non-inertial reference is introduced in the turning walk. This method can translate the turning walk into a straight-line walk when the inertial forces act on the robot. The dynamics of the robot model, called linear inverted pendulum (LIP), are changed and improved dynamics are derived to make them apply to the turning walk model. Then, we expend the new LIP model and control the zero moment point (ZMP) to guarantee the stability of the unstable parts of this model in order to generate a stable COM trajectory. We present simulation results for the improved LIP dynamics and verify the stability of the robot turning.

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Bio-Inspired Optimal Control Framework to Generate Walking Motions for the Humanoid Robot iCub Using Whole Body Models

Cited by 15 publications

References 43 publications

Special Feature on Bio-Inspired Robotics

Special Feature on Bio-Inspired Robotics

Real-Time FPGA-Based Balance Control Method for a Humanoid Robot Pushed by External Forces

Turning Gait Planning Method for Humanoid Robots

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