Programming tunable active dynamics in a self-propelled robot
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
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2023
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| _version_ | 1866929355780784128 |
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| author | Paramanick, Somnath Pal, Arnab Soni, Harsh Kumar, Nitin |
| author_facet | Paramanick, Somnath Pal, Arnab Soni, Harsh Kumar, Nitin |
| contents | We present a scheme for producing tunable active dynamics in a self-propelled robotic device. The robot moves using the differential drive mechanism where two wheels can vary their instantaneous velocities independently. These velocities are calculated by equating robot's equations of motion in two dimensions with well-established active particle models and encoded into the robot's microcontroller. We demonstrate that the robot can depict active Brownian, run and tumble, and Brownian dynamics with a wide range of parameters. The resulting motion analyzed using particle tracking shows excellent agreement with the theoretically predicted trajectories. Finally, we demonstrate that its motion can be switched between different dynamics using light intensity as an external parameter. This work opens an avenue for designing tunable active systems with the potential of revealing the physics of active matter and its application for bio- and nature-inspired robotics. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2306_06609 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Programming tunable active dynamics in a self-propelled robot Paramanick, Somnath Pal, Arnab Soni, Harsh Kumar, Nitin Soft Condensed Matter Statistical Mechanics Biological Physics We present a scheme for producing tunable active dynamics in a self-propelled robotic device. The robot moves using the differential drive mechanism where two wheels can vary their instantaneous velocities independently. These velocities are calculated by equating robot's equations of motion in two dimensions with well-established active particle models and encoded into the robot's microcontroller. We demonstrate that the robot can depict active Brownian, run and tumble, and Brownian dynamics with a wide range of parameters. The resulting motion analyzed using particle tracking shows excellent agreement with the theoretically predicted trajectories. Finally, we demonstrate that its motion can be switched between different dynamics using light intensity as an external parameter. This work opens an avenue for designing tunable active systems with the potential of revealing the physics of active matter and its application for bio- and nature-inspired robotics. |
| title | Programming tunable active dynamics in a self-propelled robot |
| topic | Soft Condensed Matter Statistical Mechanics Biological Physics |
| url | https://arxiv.org/abs/2306.06609 |