The rapid progress of molecular nanotechnology has opened the door to molecular robotics, which uses molecules as robot components. In order to promote this new paradigm, the Molecular Robotics Research Group was established in the Systems and Information Division of the Society of Instrument and Control Engineers (SICE) in 2010. The group consists of researchers from various fields including chemistry, biophysics, DNA nanotechnology, systems science and robotics, challenging this emerging new field. Last year, the group proposed a research project focusing on molecular robotics, and it was recently awarded a Grant-in-Aid for Scientific Research on Innovative Areas (FY2012-16), one of the large-scale research projects in Japan, by MEXT (Ministry of Education, Culture, Sports, Science and Technology, JAPAN). Here, we wish to clarify the fundamental concept and research direction of molecular robotics. For this purpose, we present a comprehensive view of molecular robotics based on the discussions held in the Molecular Robotics Research Group.

In this study, a Langmuir–Blodgett (LB) system has been utilized for the regulation of polymerization of a DNA origami structure at the air–water interface as a two-dimensionally confined medium, which enables dynamic condensation of DNA origami units through variation of the film area at the macroscopic level (ca. 10–100 cm²). DNA origami sheets were conjugated with a cationic lipid (dioctadecyldimethylammonium bromide, 2C₁₈N⁺) by electrostatic interaction and the corresponding LB-film was prepared. By applying dynamic pressure variation through compression–expansion processes, the lipid-modified DNA origami sheets underwent anisotropic polymerization forming a one-dimensionally assembled belt-shaped structure of a high aspect ratio although the thickness of the polymerized DNA origami was maintained at the unimolecular level. This approach opens up a new field of mechanical induction of the self-assembly of DNA origami structures.

Research on so‐called “chemical artificial intelligence” (CAI) is an emerging field with the aim of constructing information‐processing systems with learning capabilities based on chemical methodologies. This can be regarded as an attempt to reconstruct Cybernetics using molecular based systems. Many chemical reaction systems with computational abilities are proposed, but most are fixed functions that deliver molecular output for a given molecular input. On the other hand, chemical AI is a system with learning capability; namely, the output should be variable and gradually change upon repeated molecular inputs. In this paper, a compartmentalization approach for implementing cellular chemical AI using liposomes is discussed. The existing studies in terms of the methods used for assembling systems consisting of many liposomes with different functions, methods for achieving recursiveness and plasticity in chemical reaction systems, and methods for reconfiguring the network topology by liposome deformation are reviewed. Issues that must be addressed in order to realize chemical AI are also identified.