About the project
The project investigates how different types of control systems, building instructions, and building blocks affect the process of co-designing robotic bodies (morphologies) and brains (controllers). While parts of the EPEC project used real-world robots, the core methods of the COCOMO project are computer simulations of virtual robots. This allows us to investigate a much wider range of components in the design process. We also investigate the use of different types of algorithms to promote an exploratory search for new body-brain combinations, such as open-ended algorithms and quality-diversity approaches.
Sub-projects
Exploiting Stepping Stones to Evolve Efficient Robot Morphologies
Crafting robots by hand can be both difficult and time consuming. While it is possible to manually design and control robots that work in predictable environments such as factories, the task becomes daunting when the robot is introduced to the diverse conditions that exist in the real world. We want to investigate how both the morphology and controller of a robot can be evolved automatically to tackle diverse environmental conditions. Although technology has not yet reached the point where a simulated robot can be automatically or easily manufactured and put to work in the real world, we would like to take a step towards making this possible. Our main research aim is to explore how efficient robot morphologies can be created automatically, and how robots can adapt to environments they face. We will also investigate how robots evolved in simulation can be applied in the real world, and whether adaptation to diverse environmental conditions in simulation can aid the robots in adapting to conditions faced in the real world.
Bio-inspired building blocks for robot design
In this sub-project, we investigate how different building blocks can be used to compose a robotic system. This concerns the components that constitute the robotic body, such as a range of modules with different capabilities, the types of controllers they can use, and how control is communicated across the different body parts. We also study different types of building instructions, called generative encodings, which can help generate more complex robot shapes.
Software outputs
Robotics, Evolution and Modularity (REM) 2D simulation framework
Evolving Modular Robots (EMR) framework using Unity. See also tutorial held at ALIFE 2023.