Review of Recent Bio-Inspired Design and Manufacturing of Whisker Tactile Sensors

Deciphering the connection between upstream obstacles, wake structures, and root signals in seal whisker array sensing using interpretable neural networks

This study presents a novel method that combines a computational fluid-structure interaction model with an interpretable deep-learning model to explore the fundamental mechanisms of seal whisker sensing. By establishing connections between crucial signal patterns, flow characteristics, and attributes of upstream obstacles, the method has the potential to enhance our understanding of the intricate sensing mechanisms. The effectiveness of the method is demonstrated through its accurate prediction of the location and orientation of a circular plate placed in front of seal whisker arrays. The model also generates temporal and spatial importance values of the signals, enabling the identification of significant temporal-spatial signal patterns crucial for the network's predictions. These signal patterns are further correlated with flow structures, allowing for the identification of important flow features relevant for accurate prediction. The study provides insights into seal whiskers' perception of complex underwater environments, inspiring advancements in underwater sensing technologies.

Perspective for soft robotics: the field's past and future

Since its beginnings in the 1960s, soft robotics has been a steadily growing field that has enjoyed recent growth with the advent of rapid prototyping and the provision of new flexible materials. These two innovations have enabled the development of fully flexible and untethered soft robotic systems. The integration of novel sensors enabled by new manufacturing processes and materials shows promise for enabling the production of soft systems with 'embodied intelligence'. Here, four experts present their perspectives for the future of the field of soft robotics based on these past innovations. Their focus is on finding answers to the questions of: how to manufacture soft robots, and on how soft robots can sense, move, and think. We highlight industrial production techniques, which are unused to date for manufacturing soft robots. They discuss how novel tactile sensors for soft robots could be created to enable better interaction of the soft robot with the environment. In conclusion this article highlights how embodied intelligence in soft robots could be used to make soft robots think and to make systems that can compute, autonomously, from sensory inputs.

Artificial Intelligence-Empowered 3D and 4D Printing Technologies toward Smarter Biomedical Materials and Approaches

In the last decades, 3D printing has played a crucial role as an innovative technology for tissue and organ fabrication, patient-specific orthoses, drug delivery, and surgical planning. However, biomedical materials used for 3D printing are usually static and unable to dynamically respond or transform within the internal environment of the body. These materials are fabricated ex situ, which involves first printing on a planar substrate and then deploying it to the target surface, thus resulting in a possible mismatch between the printed part and the target surfaces. The emergence of 4D printing addresses some of these drawbacks, opening an attractive path for the biomedical sector. By preprogramming smart materials, 4D printing is able to manufacture structures that dynamically respond to external stimuli. Despite these potentials, 4D printed dynamic materials are still in their infancy of development. The rise of artificial intelligence (AI) could push these technologies forward enlarging their applicability, boosting the design space of smart materials by selecting promising ones with desired architectures, properties, and functions, reducing the time to manufacturing, and allowing the in situ printing directly on target surfaces achieving high-fidelity of human body micro-structures. In this review, an overview of 4D printing as a fascinating tool for designing advanced smart materials is provided. Then will be discussed the recent progress in AI-empowered 3D and 4D printing with open-loop and closed-loop methods, in particular regarding shape-morphing 4D-responsive materials, printing on moving targets, and surgical robots for in situ printing. Lastly, an outlook on 5D printing is given as an advanced future technique, in which AI will assume the role of the fifth dimension to empower the effectiveness of 3D and 4D printing for developing intelligent systems in the biomedical sector and beyond.