• The Journal of Korea Robotics Society
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• v.16 no.2
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• pp.147-154
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• 2021

One of the most challenging issues when robots interact with the environment is to establish contact quickly and avoid high impact force at the same time. The proposed method implements the passive suspension system using the redundancy of the torque-controlled robot. Instead of utilizing the actual mechanical compliance, the distal joints near the end-effector are controlled to act as a virtual spring-damper system with low feedback gains. The proximal joints are precisely controlled to push the mid-link, which is defined as the boundary link between the proximal and distal joints, towards the environment with high feedback gains. Compared to the active compliance methods, the contact force measurements or estimates are not required for contact establishment and the control time delay problems do not occur correspondingly. The proposed method was applied to the landing foot control of the 12-DoF biped robot DYROS-RED in the simulations. In the results, the impact force during landing was significantly reduced at the same collision speed.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.293-300
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• 2016

The Voice recognition is one of convenient methods to communicate between human and robots. This study proposes a speech recognition method using speech recognizers based on Hidden Markov Model (HMM) with a combination of techniques to enhance a biped robot control. In the past, Artificial Neural Networks (ANN) and Dynamic Time Wrapping (DTW) were used, however, currently they are less commonly applied to speech recognition systems. This Research confirms that the HMM, an accepted high-performance technique, can be successfully employed to model speech signals. High recognition accuracy can be obtained by using HMMs. Apart from speech modeling techniques, multiple feature extraction methods have been studied to find speech stresses caused by emotions and the environment to improve speech recognition rates. The procedure consisted of 2 parts: one is recognizing robot commands using multiple HMM recognizers, and the other is sending recognized commands to control a robot. In this paper, a practical voice recognition system which can recognize a lot of task commands is proposed. The proposed system consists of a general purpose microprocessor and a useful voice recognition processor which can recognize a limited number of voice patterns. By simulation and experiment, it was illustrated the reliability of voice recognition rates for application of the manufacturing process.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.10
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• pp.1029-1038
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• 2009

This paper proposes a gain switching algorithm for joint position control of a hydraulic humanoid robot. Accurate position control of the lower body is one of the basic requirements for robust balance and walking control. Joint position control is more difficult for hydraulic robots than it is for electric robots because of an absence of reduction gear and better back-drivability of hydraulic joints. Backdrivability causes external forces and torques to have a large effect on the position of the joints. External ground reaction forces therefore prevent a simple proportional-derivative (PD) controller from realizing accurate and fast joint position control. We propose a state feedback controller for joint position control of the lower body, define three modes of state feedback gains, and switch the gains according to the Zero Moment Point (ZMP) and linear interpolation. Dynamic equations of hydraulic actuators were experimentally derived and applied to a robot simulator. Finally, the performance of the algorithm is evaluated with dynamic simulations.