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Omnidirectional walking using central pattern generator

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Abstract

The effective and accurate walking is the biggest challenge for humanoid robot locomotion. In dynamic environments, such as RoboCup competition, not only must the speed of actions be high, but action switching must also be done almost immediately. This paper concentrates on two major behavior actions of humanoid soccer robot; straight walking and turning actions. Matsuoka central pattern generator model is used to generate trajectory actions. Both actions have their own parameters, which are obtained by comprehensive learning particle swarm optimization. By using these two actions and proper switching between them, robot can reach every point in the environment within a reasonable time. This paper tries to highlight the importance of action switching in movement maneuverability and proposes an effective solution for it. As transition from one action to another cannot be done in every posture of robot, the switching is done when robot is in double support phase. In this situation, membrane potential of each neuron has its minimum value and switching does not create big torque. The maximum time required for change action in this model is less than one step of robot. This method has been successfully implemented in rcssserver3d simulation server on NAO humanoid robot.

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Author information

Authors and Affiliations

  1. Computer Engineering and Information Technology Department, Amirkabir University of Technology, Tehran, Iran

    Karim Moradi & Saeed Shiry Ghidary

  2. Department of Computer Engineering and Information Technology, Hamedan University of Technology, Hamedan, Iran

    Mohsen Fathian

Authors
  1. Karim Moradi
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  2. Mohsen Fathian
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  3. Saeed Shiry Ghidary
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Corresponding author

Correspondence to Mohsen Fathian.

Appendix A: some properties of NAO dynamics

Appendix A: some properties of NAO dynamics

NAO is one the most humanoid robot built in 2004 by the Aldebaran Robotics company for the purpose of research and education. It has been used in RoboCup Standard Platform since 2007. Beside usability and efficiency this robot has some weak point which makes the stability control become hard.

Here, we give some properties of NAO robot which makes stability control difficult while walking and turning:

  1. 1.

    The center of mass (COM) of NAO is placed on the upper part of the robot body. The COM is the weighted average of the robot’s parts. The projection of its point on the ground can be used to estimate the robot stability. If COM is in the support area, the robot is in stable posture. Generally, the COM in all humanoid robots located in torso and upper part of robot.

  2. 2.

    The NAO robot does not have any joints in its foot tip and have a big foot in proportion to its height, so if the robot wants to walk, it has to lift its foot in the beginning of each walking cycle.

  3. 3.

    It has massive legs in contrast to the other parts of the body. This property causes a big moment when robot moves in the support phase.

  4. 4.

    The abdomen of robot is very small and robot’s heavy components, such as its power supply and on-board computer, are situated higher than the middle of the robot; so the robot stability is not good and it falls down when it tilts to each side.

  5. 5.

    Weight of the robot is not distributed equally between body parts; for example the weight of its head is about 400 g, which is almost 10 % of the total weight of its body. This results in a center of gravity near to the head of NAO.

  6. 6.

    NAO’s legs cannot rotate around the z axis with respect the body. Aside from that, robot has only transverse Hip-Yaw-Pitch joint which bent outside of robot.

  7. 7.

    Robot does not have any compensate joint. Compensate joints often use for maintain stability.

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Moradi, K., Fathian, M. & Shiry Ghidary, S. Omnidirectional walking using central pattern generator. Int. J. Mach. Learn. & Cyber. 7, 1023–1033 (2016). https://doi.org/10.1007/s13042-014-0307-4

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  • DOI: https://doi.org/10.1007/s13042-014-0307-4

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