Design and prototype of a remote arm-wrestling system

Kano, K.; Kitayama, S.; Yamamoto, Naoki; Tsutsumi, Keisuke

doi:10.1109/irds.2002.1041726

Cited by 12 publications

(5 citation statements)

References 5 publications

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“…By using this method, we can construct a remote arm wrestling systems [2] in which persons at different locations compete by communicating physical information such as force and velocity. Fig.8 shows the simplified competition system.…”

Section: Discussionmentioning

confidence: 99%

“…In an actual arm wrestling, one player can win a match by using the rotation of the forearm to the fullest [2]. The AWR-II does not include all of the degrees of freedom of human arm and hand.…”

Section: Conceptual Designmentioning

confidence: 99%

“…In the system, FS (fuzzy system) and GA (genetic algorithm) were adopted. Ryukoku University in Japan developed a forceposition input/output device [2] that can sense physical information input from a player, transmit it to a competitor, and display physical information received from the competitor. In 2004, Kagawa University and Okayama Prefectural University designed an arm wrestling system [3] [4] using a 4-DOF force display system for the analysis by synthesis of facial colour for the interaction with anthropomorphic agent.…”

Section: Introductionmentioning

confidence: 99%

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Force Analysis of Arm Wrestling Entertainment System and its Application to Control Design

Chen

Song

et al. 2006

2006 International Conference on Mechatronics and Automation

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This paper analyzes the changes in interaction force between the arm wrestling entertainment system and human hand, and presents a control strategy of force/velocity for arm wrestling robot (AWR) system. Based on the mass-springviscidity system model, the AWR control system adjusts the motor rotating direction and speed by using the information of force and angular speed feedback. This robotic machine performs arm wrestling games with people on a table. And, we can make the competition interesting by choosing the different competition rank. The system has good adaptability and the feasibility of the control method is demonstrated by the experiment results.Index Terms -AWR, Force/velocity control. Mass-springviscidity system model. Controlling force.

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Section: Discussionmentioning

confidence: 99%

Section: Conceptual Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Force Analysis of Arm Wrestling Entertainment System and its Application to Control Design

Chen

Song

et al. 2006

2006 International Conference on Mechatronics and Automation

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“…The sensors can be designed in single or integrated in the mechanical arm straightly [8]. Through our careful analysis of actions in arm wrestling games, we choose the second scheme.…”

Section: Structure Of Mechanical Armmentioning

confidence: 99%

“…Much interesting and elaborate research had been done by scholars in many fields at home or overseas. Ryukoku University developed a force-position input/output device [2] that can sense physical information input from a player, transmit it to a competitor, and display physical information received from the competitor. Minoru Hashimoto (2002) developed a robot arm with joint torque sensing capability.…”

Section: Introductionmentioning

confidence: 99%

Design, Fabrication and Application of ARm Wrestling Robot

Gao

Song

Lei

et al. 2006

2006 International Conference on Mechatronics and Automation

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This paper presents a novel 2 DOF robotic arm wrestling system integrated with mechanical arm, elbow/wrist force sensors, servo motor, encoder, 3-D MEMS accelerometer, and USB camera. The arm wrestling robot (AWR) is used to play arm wrestling game with human for entertainment. Based on the force testing equipment, we acquire the data of surface electromyographic (EMG) signals form target muscle when a real player competes with the robot. Wavelet transform and neural network are applied to extract the characteristics of EMG signals and estimate the joint torque. Experiment results have proved the validation of the wavelet neural network method.

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