Robotic materials: Leveraging mechanics and soft materials to achieve unprecedented capabilities
Co-Chairs:
Maurizio Chiaramonte, Facebook Reality Labs
Yiğit Mengüç, Facebook Reality Labs
Chiara Daraio, California Institute of Technology
Katia Bertoldi, Harvard University
Tianshu Liu, Facebook Reality Labs
Summary:
The goal of this mini-symposium is to apply the lens of mechanics to material robotics research. The latter is a rapidly emerging area of research where design of novel multi-functional materials (harnessing material properties and/or meta-structures) enables unprecedented capabilities and robustness of soft autonomous machines. Soft robots have the ability to drastically impact many fields of engineering and science alike, with applications ranging from space exploration to medicine. Examples of the many capabilities of soft robots include being able to robustly interact with unstructured environments thanks to high compli- ance, withstand crushing hydrostatic pressures while carrying out tasks, crawl through arbitrarily small and tortuous cavities via shape-morphing, provide (in the form of actuated fabrics) non-obstructive exoskeleta, as well as artificial muscles. Such capabilities are achieved through a tight integration of material compliance, sensing, and actuation. The mini-symposium aims at bringing together researchers addressing the fundamental challenges in robotics (namely power, actuation, sensing, control, and structure) by designing novel materials and structures, exploiting multiple-physics and leveraging properties at disparate length and time scales. In addition, an objective of the mini-symposium is to explore structured and rational design methodologies for replication and generalization of specific capabilities.
Researchers in the field are encouraged to partake in this symposium, where potential research topics are:
– Functional materials
– Metamaterials
– Multi-physics actuations
– Structural instabilities as actuation mechanism
– Biomimetic/bio-inspired soft materials & structures
– Computational modeling, design optimization, and controls