Toward Perceptive Soft Robots: Progress and Challenges

By Hongbo Wang, M. Totaro, Lucia Beccai. Advancement of science, 2018

684 citations recorded by the source corpus.

In the past few years, soft robotics has rapidly become an emerging research topic, opening new possibilities for addressing real‐world tasks. Perception can enable robots to effectively explore the unknown world, and interact safely with humans and the environment. Among all extero‐ and proprioception modalities, the detection of mechanical cues is vital, as with living beings. A variety of soft sensing technologies are available today, but there is still a gap to effectively utilize them in soft robots for practical applications. Here, the developments in soft robots with mechanical sensing are summarized to provide a comprehensive understanding of the state of the art in this field. Promising sensing technologies for mechanically perceptive soft robots are described, categorized, and their pros and cons are discussed. Strategies for designing soft sensors and criteria to evaluate their performance are outlined from the perspective of soft robotic applications. Challenges and trends in developing multimodal sensors, stretchable conductive materials and electronic interfaces, modeling techniques, and data interpretation for soft robotic sensing are highlighted. The knowledge gap and promising solutions toward perceptive soft robots are discussed and analyzed to provide a perspective in this field.

Subfields: Biomedical Engineering, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/431510d3baa67ac6e33062b2d233891138848fc1

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In Biomedical Engineering

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Citations in the corpus

Model-Based Control of Soft Robots: A Survey of the State of the Art and Open Challenges (2021, background): “r ^ ^ c ^ h h hm (17) Model-Based Perception of Shape and Forces Despite the many advances in designing and fabricating soft sensors [9], the perception problem remains an open”
ReSkin: versatile, replaceable, lasting tactile skins (2021, background): “Resistive and capacitive soft sensors require many connections that lead to early failure and integration challenges [4, 5].”
Soft robot perception using embedded soft sensors and recurrent neural networks (2019, background): “Furthermore, in the case of interactions with the surroundings, contact modeling is a highly complex mathematical problem, currently limited to theoretical studies (5).”
MakeSense: Automated Sensor Design for Proprioceptive Soft Robots (2019, neutral): “The behavior of soft robots made of a single or several soft silicones or urethanes is well-captured by standard hyperelastic material models 54 .”