Animals exhibit a wide variety of morphologies and sensors, believed to have appeared through billions of years of evolution. Common examples relevant to vision include differences in pupil shapes, the positioning of eyes, various types of eyes, and a varying level of multimodality across animals. Such adaptations are hypothesized to be instances of the so-called Ecological Theory, which posits a strong connection between the specifics of vision and the environment surrounding the agent, its objectives, and its body. How can we replicate this diversity and achieve adaptive design in robotics and vision systems?

In this tutorial, we discuss I) alternative forms of visual sensors that can be useful for real-world robots and II) computational approaches to robot and vision design that can achieve the goal of adaptive design automatically, effectively, and efficiently. The tutorial covers topics in sensing, control, simulation, optimization, and learning-based design for various rigid and soft robots and visual sensors. The material is drawn from state-of-the-art breakthroughs in the field and insights from other disciplines.

This material is accessible to individuals of all backgrounds and levels of expertise.