SIMULATING A SEMI-AUTOMATIC MOTION CONTROL MODE OF BIPEDAL WALKING ROBOTS IN VIRTUAL ENVIRONMENT SYSTEMS
Abstract and keywords
Abstract (English):
The paper considers methods and approaches for semi-automatic motion control of bipedal walking robots in virtual environment systems. The proposed solutions include generating a walking pattern, calculating inverse kinematics, and synthesis of PD-controllers with feedback based on the angle sensor readings. To ensure the static and dynamic stability of the walking robot, generating its movement trajectories is implemented using the criterion of zero mo-ment point (ZMP) and the inverse pendulum model with virtual height. In this case, the walking pattern is generated by solving the problem of inverse kinematics using the Leven-berg-Marquardt method to calculate the rotation angles in the robot joints. To implement semi-automatic motion control of a walking robot in a virtual environment, an approach based on the technology of functional diagrams and virtual control panels is used. Testing the proposed methods and approaches is carried out in the VirSim virtual environment software package and shows their adequacy and efficiency for modelling a walking robot movement while maintaining its balance.

Keywords:
bipedal walking robot, simula-tion, walking pattern, stability, zero moment point, inverse kinematics, virtual console, PD controller, virtual environment system.
Text
Text (PDF): Read Download
References

1. Yurevich E.I. Fundamentals of Robotics. St. Petersburg: BHV-Petersburg; 2017.

2. Geijtenbeek T., Van de Panne M., Frank van der Stappen A. Flexible Muscle-Based Locomotion for Bipedal Creatures. ACM Transactions on Graphics 32. 2013 (6). doi:https://doi.org/10.1145/2508363.2508399.

3. Mombauri K., Berns K. Modelling, Simulation and Optimization of Bipedal Walking. Springer; 2013.

4. Kajita S, Benallegue M, Cisneros R, Sakaguchi T, Nakaoka S, Morisawa M, Kaneko K, Kanehiro F. Biped Walking Pattern Generation Based on Spatially Quantized Dynamics. In: Proceedings of IEEE-RAS 17th International Conference on Humanoid Robotics; Birmingham (UK): 2017. p. 599-605. doi:https://doi.org/10.1109/HUMANOIDS.2017.8246933.

5. Westervelt E., Grizzle J., Chevallereau C., Choi J., Morris B. Feedback Control of Dy-namic Bipedal Robot Locomotion, ser. Control and Automation. Boca Raton: CRC Press; 2007.

6. Vukobratovic M., Borovac B. Zero-Moment Point - Thirty-Five Years of Its Life. International Journal of Humanoid Robotics. 2004;1:157-173. doi:https://doi.org/10.1142/S0219843604000083.

7. Ha T., Choi C.-H. An Effective Trajectory Generation Method for Bipedal Walking. Ro-botics and Autonomous Systems. 2007;55:795-810. doi:https://doi.org/10.1016/j.robot.2007.06.001.

8. Mikhailyuk M.V., Maltsev A.V., Timokhin P.Yu., Strashnov E.V., Kryuchkov B.I., Usov V.M. VirSim Virtual Environment System for Simulation Training Complexes for Cosmonaut Training. Manned Spaceflight Scientific Periodical. 2020;37(4):72-95. doi:https://doi.org/10.34131/MSF.20.4.72-95.

9. Strashnov EV, Mironenko IN, Finagin LA. Command Mode for Virtual Bipedal Walking Robot Control. In: Proceedings of NIISI RAS: 2020;10(4). p. 33-39.

10. Sugihara T. Solvability-Unconcerned Inverse Kinematics Based on Levenberg-Marquardt Method with Robust Damping. In: Proceedings of the 9th IEEE-RAS International Conference on Humanoid Robots; Paris (France): 2009. p. 555-560. doi:https://doi.org/10.1109/ICHR.2009.5379515.

Login or Create
* Forgot password?