Materializing Autonomy in Soft Robots across Scales

Article

关键词: DATA-DRIVEN CONTROL;    CO-DESIGN PROBLEMS;    SELF-ORGANIZATION;    CONTINUUM ROBOTS;    DYNAMIC CONTROL;    MODEL;    INTELLIGENCE;    MANIPULATOR;    MATTER;    REAL;   

DOI  :  10.1002/aisy.202300111

来源: SCIE

【 摘 要 】

The impressive capabilities of living organisms arise from the way autonomy is materialized by their bodies. Across scales, living beings couple computational or cognitive intelligence with physical intelligence through body morphology, material multifunctionality, and mechanical compliance. While soft robotics has advanced the design and fabrication of physically intelligent bodies, the integration of information-processing capabilities for computational intelligence remains a challenge. Consequently, perception and control limitations have constrained how soft robots are built today. Progress toward untethered autonomy will require deliberate convergence in how the field codevelops new materials, fabrication methods, and control strategies for soft robots. Here, a new perspective is put forward: that researchers should use tasks alone to impose material and information constraints on soft robot design. A conceptual framework is proposed for a task-first design paradigm that sidesteps limitations imposed by control strategies. This framework allows emergent synergies between material and information processing properties of soft matter to be readily exploited for task-capable agents. Particular attention is paid to the scale dependence of solutions. Finally, an outlook is presented on emerging research opportunities for achieving autonomy in future soft robots as large as elephant trunks and as small as paramecia.