The morphology and structure play a crucial role in shaping the behavior and functionality of both biological and robotic systems. In this work, we are inspired by morphogenesis, a fundamental biological process that encompasses the emergence of organs and organism morphology. It is driven by both internal and environmental factors and profoundly influences cellular behavior during development. By studying the environmental-driven properties that give rise to specific cellular morphologies, we investigate how control of the environment can be harnessed to trigger structural changes. Furthermore, we explore the potential application of these principles to inspire the development of robots with predefined morphologies. However, this endeavor is inherently stochastic and challenging to simulate accurately. To address this complexity, we propose leveraging a Markov decision process-inspired controller, guided by a Markov model. Using this approach, we can design scalable robotic systems capable of reconfiguring their morphologies and exhibiting diverse motion characteristics in response to environmental cues.