Introduction
This project addresses critical sustainability challenges in robotics by developing physical computing systems that eliminate dependence on semiconductor electronics.
Current robots rely heavily on microprocessors for information processing and control, creating substantial supply chain vulnerabilities and electronic waste at end-of-life. Additionally, semiconductor electronics cannot function in hazardous environments such as gamma radiation zones, limiting robotic deployment.
This project pioneers the development of physical computing blocks for robot control and information processing made entirely from soft, biodegradable materials.
This involves creating central pattern generators, sensory receptors (for sensing contact, light, etc.), logic gates, higher-order decision circuits utilising interactions between soft structures eliminating the need for microcontrollers or semiconductors. Building on recent unpublished results from Dr. Godaba’s group on electronics-free electrofluidic nervous systems, the work draws inspiration from information processing in simple invertebrates. The goal is to design minimal, efficient systems capable of processing sensory inputs and generating control signals to operate multi-actuator soft robots.
Research Outcomes and Candidates
This project will pave the foundation for fully soft and biodegradable robots that can sense and compute without the need for semiconductor electronics, relying on computation by mechanical structures. In the long term, these foundational blocks can help create robots that can harvest energy from nature, conduct functional tasks and biodegrade completely. The approach addresses multiple sustainability challenges: eliminating electronic waste, reducing supply chain dependencies, enabling operation in hazardous environments, and creating truly sustainable robotic systems.
This project is suitable for students interested in hands-on fabrication of novel soft robots. The project offers significant creative opportunities in developing novel computational architectures and robot design.
References:
References
Sitti M. Physical intelligence as a new paradigm. Extreme Mech Lett. 2021 Apr 26;46:101340.
M. Garrad et al. A soft matter computer for soft robots. Sci. Robot.4,eaaw6060(2019). DOI:10.1126/scirobotics.aaw6060