Stable whole-body motion generation for humanoid robots to imitate human motions

Kim, Seungsu; Kim, ChangHwan; You, Bum-Jae; Oh, Sang–Rok

doi:10.1109/iros.2009.5354271

Cited by 74 publications

(36 citation statements)

References 16 publications

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“…Kim et al [8] investigated how to keep the stability when converting a motion from a human to a robot. This study used a complex calculation that confirmed the stability of the robot, both kinetically and dynamically.…”

Section: Proposed Methodsmentioning

confidence: 99%

Converting Motion between Different Types of Humanoid Robots Using Genetic Algorithms

Nishiyama¹,

Iba²

2015

IJCTE

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Abstract-The imitation between different types of robots remains an unsolved task for a long time. The assignment of the correct angles to each joint is critical for robot motion. However, different robots have different structures, thus this discrepancy causes a difficulty when converting a motion to another type of robot. For solving this problem, we propose a GA-based method that can find the conversion matrix needed to map joint angles of one robot to another. There are two objectives to consider when creating an imitation; reducing the difference between the ideal imitation and the converted imitation and keeping the stability. Three experiments were conducted; a stable experiment, an unstable experiment and a double learning experiment. As a result, the double experiment showed a high concordance rate of 93.5%, the highest stability and the fastest speed of all experiments. These results show great promise for the proposed method as a way to realize motion imitation between different types of robots.

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Section: Proposed Methodsmentioning

confidence: 99%

Converting Motion between Different Types of Humanoid Robots Using Genetic Algorithms

Nishiyama¹,

Iba²

2015

IJCTE

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“…The errors caused by model error and environment disturbance are eliminated utilizing posture balance algorithm [1]. Due to high-performance trajectory tracking of electrical motors, many humanoid robots are capable of stable walking and running [2,3]. However, these robots tend to be energetically inefficient and brittle against terrain disturbance.…”

Section: Introductionmentioning

confidence: 99%

Design of a biped robot actuated by pneumatic artificial muscles

Liu

Zang

Liu

et al. 2015

BME

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Abstract. High compliant legs are essential for the efficient versatile locomotion and shock absorbency of humans. This study proposes a biped robot actuated by pneumatic artificial muscles to mimic human locomotion. On the basis of the musculoskeletal architecture of human lower limbs, each leg of the biped robot is modeled as a system of three segments, namely, hip joint, knee joint, and ankle joint, and eleven muscles, including both monoarticular and biarticular muscles. Each rotational joint is driven by a pair of antagonistic muscles, enabling joint compliance to be tuned by operating the pressure inside the muscles. Biarticular muscles play an important role in transferring power between joints. Walking simulations verify that biarticular muscles contribute to joint compliance and can absorb impact energy when the robot makes an impact upon ground contact.

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“…The general pipeline of balance maintenance involves designing ZMP trajectory for a humanoid robot, computing reference CoM trajectory from the ZMP trajectory, and constraining a humanoid robot to follow the reference CoM trajectory. Kim et al [23] proposed a method for imitating full body dance movements. The ZMP trajectory of the robot was generated based on the support region and used to compute reference CoM trajectory by recursive equations.…”

Section: Introductionmentioning

confidence: 99%

“…To this end, several methods which performed optimization to minimize error between movements of human and a humanoid robot and interpolation between discrete time points have been proposed [16,19,20,21]. For example, Kim et al [23] optimized joint angle trajectories to minimize error between movements of human and a humanoid robot; then applied spline interpolation to smooth angle trajectories of upper body. Boutin et al [26] formulated inverse kinematics as an optimization problem to find joint angles for walking that satisfy motion constraints.…”

Section: Introductionmentioning

confidence: 99%