About this Research Topic
Recent advances in additive manufacturing techniques, particularly three-dimensional (3D) printing and four-dimensional (4D) printing have enabled the production of different parts of robots, including sensors and actuators with high multifunctionality, compliance, and manufacturing flexibility unlike in conventional approaches. Based on pre-programmed architecture that are often inspired by biological structures, 4D-printed robots and soft robots are adaptive mechanisms responding to external stimuli, like temperature, force, electricity, light, and humidity made with polymeric based composites. They can be applied in a wide range of applications in medical assisted robots, automotive, aerospace, microfluidics, tissue engineering, drug delivery, and wearable electronics. The design and prediction of behavior and control of these products is yet a complex problem requiring the multiphysics formulation where machine learning and deep learning techniques have been promising.
This Research Topic aims to promote the dissemination of recent advances in additive manufacturing of soft robots including sensors, actuators, energy generators, morphology control and novel design strategies (machine learning/ deep learning).
The Research Topic creates a forum for research contributions covering a broad spectrum of topics ranging from computational and experimental investigations to hybrid approaches in the research and development of advanced robotics and additive manufacturing technologies. All researchers/investigators are invited to contribute to this Research Topic with their original research articles, short communications, and review articles.
4D-printed soft robots, sensor, and actuators
• Bioinspired design 4D printing
• Stimuli-responsive polymers, hydrogels, and polyelectrolytes
• 4D printing and 4D bioprinting of soft robots
• Smart materials in soft robotics and additive manufacturing
• Modeling and control of 4D-printed structures
• Machine learning, reinforcement learning, and deep learning models for designing 3D/4D printed robots
This Research Topic aims to promote the dissemination of recent advances in additive manufacturing of soft robots including sensors, actuators, energy generators, morphology control and novel design strategies (machine learning/ deep learning).
The Research Topic creates a forum for research contributions covering a broad spectrum of topics ranging from computational and experimental investigations to hybrid approaches in the research and development of advanced robotics and additive manufacturing technologies. All researchers/investigators are invited to contribute to this Research Topic with their original research articles, short communications, and review articles.
4D-printed soft robots, sensor, and actuators
• Bioinspired design 4D printing
• Stimuli-responsive polymers, hydrogels, and polyelectrolytes
• 4D printing and 4D bioprinting of soft robots
• Smart materials in soft robotics and additive manufacturing
• Modeling and control of 4D-printed structures
• Machine learning, reinforcement learning, and deep learning models for designing 3D/4D printed robots
Keywords: 4D Printing, 3D Printing, Soft Robotics, Sensors, Actuators
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
