MORS: BLDC based small sized quadruped robot

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The article describes the mechanical design, electronics and control software of the new quadruped robot MORS. The robot is intended for education and research fields. It is relatively small and lightweight and has modular design to simplify production and assembly. The robot is driven by brushless DC motors governed by the Field-Oriented Control. The trot gait is chosen as the basic one. The locomotion control algorithm is based on Zero Moment Point Preview Control method. The desired zero moment point is generated by tracking the intersection of projections of diagonally opposite legs. Software of the robotic platform is completely open sourced. To test the performance of all robot components, a number of experiments were conducted both in simulation and on the hardware platform. The experimental results demonstrate the efficiency of the robot walking in different directions with velocity up to 1.2 m/s and a load capacity of up to 7 kg, which is almost equal to its own weight.

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Sobre autores

V. Budanov

Lomonosov Moscow State University

Autor responsável pela correspondência
Email: vldanilov90@gmail.com

Institute of Mechanics

Rússia, Moscow

V. Danilov

Lomonosov Moscow State University

Email: vldanilov90@gmail.com

Institute of Mechanics

Rússia, Moscow

D. Kapytov

Lomonosov Moscow State University

Email: vldanilov90@gmail.com

Institute of Mechanics

Rússia, Moscow

K. Klimov

Lomonosov Moscow State University

Email: vldanilov90@gmail.com

Institute of Mechanics

Rússia, Moscow

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2. Fig. 1. Photograph of the MORS robot.

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3. Fig. 2. Robot layout diagram.

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4. Fig. 3. Robot dimensions.

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5. Fig. 4. Main units of the robot leg.

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6. Fig. 5. Main units of the electric drive.

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7. Fig. 6. Electronic unit interaction diagram.

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8. Fig. 7. Software architecture.

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9. Fig. 8. Structural diagram of the locomotion control algorithm.

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10. Fig. 9. Direction of robot movement.

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11. Fig. 10. Robot rotation.

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12. Fig. 11. The trajectory of the robot's foot during walking in projection onto the vertical plane Oxz.

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13. Fig. 12. Formation of a smooth trajectory of the foot with a sudden change in the final point pfinish in projection onto the Ox axis. The dotted line indicates the moments of time when the change in the pfinish point occurred.

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14. Fig. 13. Model of the trolley on the table.

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15. Fig. 14. Projection of the robot on the horizontal plane during trot movement.

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16. Fig. 15. Generated desired ZMP trajectory in projection on the horizontal plane.

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17. Fig. 16. Structural diagram of the ZMP preview control system.

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18. Fig. 17. ZMP and CM trajectories obtained as a result of modeling for the expected movement along the longitudinal axis.

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19. Fig. 18. Change in the coefficient G(i) depending on the predicted number of time steps.

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20. Fig. 19. Graphic visualization in the PyBullet environment of the robot walking at a trot.

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21. Fig. 20. The first test in the virtual environment. Robot movement along the longitudinal axis with the desired speed υx = 0.4 m/s.

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22. Fig. 21. The second test in the virtual environment. Robot movement with a constantly increasing desired speed υx.

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23. Fig. 22. The third test in the virtual environment. Robot movement with changing values of the desired speeds υx and υy.

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24. Fig. 23. The fourth test in the virtual environment. The trajectory of the robot's CM during testing the robot's ability to turn around the vertical axis.

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25. Fig. 24. The first test of the hardware platform. Robot movement along the longitudinal axis with the desired speed υx = 0.4 m/s.

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26. Fig. 25. The second test of the hardware platform. Robot movement with a constantly increasing desired speed υx.

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27. Fig. 26. The robot during tests for load capacity.

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