Fluidically Innervated Lattices Make Versatile and Durable Tactile Sensors
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arXiv
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| Format: | Preprint |
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2025
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| author | Zhang, Annan Flores-Acton, Miguel Yu, Andy Gupta, Anshul Yao, Maggie Rus, Daniela |
| author_facet | Zhang, Annan Flores-Acton, Miguel Yu, Andy Gupta, Anshul Yao, Maggie Rus, Daniela |
| contents | Tactile sensing plays a fundamental role in enabling robots to navigate dynamic and unstructured environments, particularly in applications such as delicate object manipulation, surface exploration, and human-robot interaction. In this paper, we introduce a passive soft robotic fingertip with integrated tactile sensing, fabricated using a 3D-printed elastomer lattice with embedded air channels. This sensorization approach, termed fluidic innervation, transforms the lattice into a tactile sensor by detecting pressure changes within sealed air channels, providing a simple yet robust solution to tactile sensing in robotics. Unlike conventional methods that rely on complex materials or designs, fluidic innervation offers a simple, scalable, single-material fabrication process. We characterize the sensors' response, develop a geometric model to estimate tip displacement, and train a neural network to accurately predict contact location and contact force. Additionally, we integrate the fingertip with an admittance controller to emulate spring-like behavior, demonstrate its capability for environment exploration through tactile feedback, and validate its durability under high impact and cyclic loading conditions. This tactile sensing technique offers advantages in terms of simplicity, adaptability, and durability and opens up new opportunities for versatile robotic manipulation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_21225 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Fluidically Innervated Lattices Make Versatile and Durable Tactile Sensors Zhang, Annan Flores-Acton, Miguel Yu, Andy Gupta, Anshul Yao, Maggie Rus, Daniela Robotics Machine Learning Systems and Control Tactile sensing plays a fundamental role in enabling robots to navigate dynamic and unstructured environments, particularly in applications such as delicate object manipulation, surface exploration, and human-robot interaction. In this paper, we introduce a passive soft robotic fingertip with integrated tactile sensing, fabricated using a 3D-printed elastomer lattice with embedded air channels. This sensorization approach, termed fluidic innervation, transforms the lattice into a tactile sensor by detecting pressure changes within sealed air channels, providing a simple yet robust solution to tactile sensing in robotics. Unlike conventional methods that rely on complex materials or designs, fluidic innervation offers a simple, scalable, single-material fabrication process. We characterize the sensors' response, develop a geometric model to estimate tip displacement, and train a neural network to accurately predict contact location and contact force. Additionally, we integrate the fingertip with an admittance controller to emulate spring-like behavior, demonstrate its capability for environment exploration through tactile feedback, and validate its durability under high impact and cyclic loading conditions. This tactile sensing technique offers advantages in terms of simplicity, adaptability, and durability and opens up new opportunities for versatile robotic manipulation. |
| title | Fluidically Innervated Lattices Make Versatile and Durable Tactile Sensors |
| topic | Robotics Machine Learning Systems and Control |
| url | https://arxiv.org/abs/2507.21225 |