Programming tunable active dynamics in a self-propelled robot

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...

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Bibliographic Details
Published inThe European physical journal. E, Soft matter and biological physics Vol. 47; no. 5; p. 34
Main Authors Paramanick, Somnath, Pal, Arnab, Soni, Harsh, Kumar, Nitin
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 23.05.2024
Springer Nature B.V
Subjects
Biological and Medical Physics
Biophysics
Complex Fluids and Microfluidics
Complex Systems
Equations of motion
Luminous intensity
Nanotechnology
Obstacle avoidance
Parameters
Particle tracking
Physics
Physics and Astronomy
Polymer Sciences
Regular Article - Flowing Matter
Robot dynamics
Robotics
Robots
Soft and Granular Matter
Surfaces and Interfaces
Thin Films
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Summary: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. Later, we show that its motion can be switched between different dynamics using light intensity as an external parameter. Intriguingly, we demonstrate that the robot can efficiently navigate through many obstacles by performing stochastic reorientations driven by the gradient in light intensity towards a desired location, namely the target. 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. Graphical abstract
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ISSN:1292-8941
1292-895X
DOI:10.1140/epje/s10189-024-00430-x