Kinematic synthesis using reinforcement learning
Kaz Vermeer (Student TU Delft)
Reinier Kuppens (TU Delft - Mechanical Engineering)
Just Herder (TU Delft - Mechanical Engineering, TU Delft - Mechanical Engineering)
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Abstract
The presented research demonstrates the synthesis of two-dimensional kinematic mechanisms using feature-based reinforcement learning. As a running example the classic challenge of designing a straight-line mechanism is adopted: a mechanism capable of tracing a straight line as part of its trajectory. This paper presents a basic framework, consisting of elements such as mechanism representations, kinematic simulations and learning algorithms, as well as some of the resulting mechanisms and a comparison to prior art. Series of successful mechanisms have been synthesized for path generation of a straight line and figure-eight.