Soft Robot and Genetic Evolution
Induced gravitation and friction in a robot simulation, to create a highly realistic and dynamic environment for the robot to operate in, giving me the ability to fine-tune its performance.
Utilized simulation techniques and 3D graphics Python module, VPython to simulate a spring-mass framed soft robot to evolve its gait through optimization techniques like random search, hill climbing, and genetic evolution optimization.
Induced gravitation and friction to create a realistic environment for the robot to operate in.
Optimized the genetic evolution parameters to achieve a maximum speed of 17.5 cm/sec over a 30 minute runtime.
This project showcases the power of advanced simulation techniques, 3D graphics software tools, and robotics optimization for evolving the gait of soft robots.
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