• Proceedings of the KSME Conference
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• 2005.11a
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• pp.201.2-201.2
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• 2005

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.10a
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• pp.153-154
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• 2009

• Journal of the Korean Society for Precision Engineering
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• v.23 no.7 s.184
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• pp.24-29
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• 2006

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2011.06a
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• pp.297-298
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• 2011

• Journal of the Korean Society of Industry Convergence
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• v.21 no.1
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• pp.17-27
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• 2018

We propose a new approach to control a biped robot motion based on iterative learning of voice command for the implementation of smart factory. The real-time processing of speech signal is very important for high-speed and precise automatic voice recognition technology. Recently, voice recognition is being used for intelligent robot control, artificial life, wireless communication and IoT application. In order to extract valuable information from the speech signal, make decisions on the process, and obtain results, the data needs to be manipulated and analyzed. Basic method used for extracting the features of the voice signal is to find the Mel frequency cepstral coefficients. Mel-frequency cepstral coefficients are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. The reliability of voice command to control of the biped robot's motion is illustrated by computer simulation and experiment for biped walking robot with 24 joint.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2493-2503
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• 2018

Passive dynamic walking exhibits humanoid and energy efficient gaits. However, optimal design of passive walker at multi-variable level is not well studied yet. This paper presents a Chaotic Particle Swarm Optimization (CPSO) algorithm and applies it to the optimal design of flexible passive walker. Hip torsional stiffness and damping were incorporated into flexible biped walker, to imitate passive elastic mechanisms utilized in human locomotion. Hybrid dynamics were developed to model passive walking, and period-one gait was gained. The parameters global searching scopes were gained after investigating the influences of structural parameters on passive gait. CPSO were utilized to optimize the flexible passive walker. To improve the performance of PSO, multi-scroll Jerk chaotic system was used to generate pseudorandom sequences, and chaotic disturbance would be triggered if the swarm is trapped into local optimum. The effectiveness of CPSO is verified by comparisons with standard PSO and two typical chaotic PSO methods. Numerical simulations show that better fitness value of optimal design could be gained by CPSO presented. The proposed CPSO would be useful to design biped robot prototype.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.33 no.10
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• pp.1014-1022
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• 2009

A biped robot in locomotion can be regarded to be kinetically redundant in that the link-chain from its foot on the ground to its swing foot has more degrees of freedom that needed to realize stable bipedal locomotion. This paper proposes a new method to generate a trajectory for bipedal locomotion based on this redundancy, which directly generates a locomotion trajectory at the joint level unlike some other methods such as LIPM (linear inverted-pendulum mode) and GCIPM (gravity-compensated inverted-pendulum mode), each of which generates a trajectory of the center of gravity or the hip link under the assumption of the dominance of the hip-link inertia before generating the trajectory of the whole links at the joint level. For the stability of the trajectory generated in the proposed method, a stability condition based on the ZMP (zero-moment point) is used as a constraint as well as other kinetic constraints for bipedal motions. A 6-DOF biped robot is used to show how a stable locomotion trajectory can be generated in the sagittal plane by the proposed method and to demonstrate the feasibility of the proposed method.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1216-1222
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• 2009

This article describes a simple method for generating the walking trajectory for the biped humanoid robot. The method used a simple inverted model instead of complex multi-mass model and a reasonable explanation for the model simplification is included. The problem of gait trajectory generation is to find the solution from the desired ZMP trajectory to CoG trajectory. This article presents the analytic solution for the bipedal gait generation on the bases of ZMP trajectory. The presented ZMP trajectory has Fourier series form, which has finite or infinite summation of sine and cosine functions, and ZMP trajectory can be designed by calculating the coefficients. From the designed ZMP trajectory, this article focuses on how to find the CoG trajectory with analytical way from the simplified inverted pendulum model. Time segmentation based approach is adopted for generating the trajectories. The coefficients of the function should be designed to be continuous between the segments, and the solution is found by calculating the coefficients with this connectivity conditions. This article also has the proof and the condition of solution existence.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.546-551
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• 2011

Tilt sensor is required to control the attitude of the biped robot when it walks on an uneven terrain. Vision sensor, which is used for recognizing human or detecting obstacles, can be used as a tilt angle sensor by comparing current image and reference image. However, vision sensor alone has a lot of technological limitations to control biped robot such as low sampling frequency and estimation time delay. In order to verify limitations of vision sensor, experimental setup of an inverted pendulum, which represents pitch motion of the walking or running robot, is used and it is proved that only vision sensor cannot control an inverted pendulum mainly because of the time delay. In this paper, to overcome limitations of vision sensor, Kalman filter for the multi-rate sensor fusion algorithm is applied with low-quality gyro sensor. It solves limitations of the vision sensor as well as eliminates drift of gyro sensor. Through the experiment of an inverted pendulum control, it is found that the tilt estimation performance of fusion sensor is greatly improved enough to control the attitude of an inverted pendulum.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.183-192
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• 2016

Generating motion of center of mass for biped robots is a challenging issue since biped robots can easily lose balance due to limited contact area between foot and ground. In this paper, we propose force control method to generate high-speed motion of the center of mass for horizontal direction without losing balancing condition. Contact consistent multi-body dynamics of the robot is used to calculate force for horizontal direction of the center of mass considering balance. The calculated force is applied for acceleration or deceleration of the center of mass to generate high speed motion. The linear inverted pendulum model is used to estimate motion of the center of mass and the estimated motion is used to select either maximum or minimum force to stop at goal position. The proposed method is verified by experiments using 12-DOF torque controlled human sized legged robot.