1. Abstract
Current pressure and temperature sensing methods face challenges such as crosstalk, low integration, and difficulties in achieving large-scale arrays, which significantly hinder the practical application value of multifunctional bionic sensors in intelligent bionic robots. In this study, the authors propose a novel multifunctional bionic electronic palm system (BEPS), composed of 16 dual-mode decoupled bionic electronic skins (e-skins). Through the ingenious introduction of vertical stacking design and the manufacturing techniques of in-situ photopolymerization and 3D printing, a large-scale array integration with high sensing performance is constructed. Additionally, a universal decoupling computational model is developed to achieve non-crosstalk sensing of temperature and pressure. To demonstrate the practical application value of the proposed bionic palm, three exemplary applications are implemented, showing that the robotic hand can detect water temperature and water level, as well as confirm the softness and shape of grasped objects. The BEPS system, combined with neural hand contraction reflexes, enables closed-loop control and feedback when handling hot and cold objects. This advancement holds great potential in enhancing the functionality and adaptability of robotic systems.
II. Background Introduction
The human hand is a crucial organ for perceiving the external world, with each joint participating in various precise operations. The hand can detect stimuli such as temperature, pressure, humidity, texture, vibration, and pain, particularly pressure and temperature. Currently, numerous studies are dedicated to developing devices capable of simulating pressure and temperature. For instance, Ren et al. designed a flexible multilayer continuous pressure positioning sensor based on a combined bionic strategy, achieving pressure simulation. Meanwhile, Zhang et al. utilized thermal-induced ion migration dynamics and electrically induced cation implantation mechanisms to enable temperature sensing in an asymmetric bilayer composed of nonionic polymers and polyelectrolyte layers. The perception of pressure in the human hand is achieved through pressure receptors in the skin, such as Merkel cells and Pacinian corpuscles, while temperature perception is mediated by thermoreceptors (e.g., heat and cold receptors) in nerve endings. In fact, these receptors, located within the limited space of the skin, can independently receive and process information without mutual interference due to the selective sensitivity of neural receptors. Additionally, each type of receptor signal in the nervous system has dedicated pathways, with distinct nerve fibers transmitting temperature and pressure signals separately. This "division of labor" mechanism ensures that different types of sensory signals operate independently and reach the brain without cross-interference, enabling humans to accurately perceive environmental information and its changes. Unfortunately, current research still largely relies on a single device to achieve simultaneous perception of temperature and pressure. For example, Chen et al. explored a high-performance pressure sensor that can respond to both temperature and pressure stimuli through the combination of functionalized carbon nanotubes and flexible modified silicone rubber. However, the proposed sensor exhibits significant cross-sensitivity between temperature and pressure signals. Overcoming this cross-sensitivity, decoupling interference, and achieving independent sensing of both signals remain critical challenges in ongoing research. Therefore, to achieve more advanced, precise, and profound bionics, it is essential to highly accurately mimic this "division of labor.".
In this study, the authors developed a bionic electronic palm system (BEPS) for dual-mode decoupled sensing of temperature and pressure, consisting of a 16-array of dual-mode decoupled bionic (BDB) electronic skin. The BDB electronic skin features a vertically stacked, highly integrated design of temperature and pressure sensing units through a double-layer flexible printed circuit board (FPCB) structure (see Fig. 1b(iii)). The pressure sensing unit employs a uniformly layered micro-cone structure, enabling ultra-capacitive ionic pressure sensing via 3D printing technology. The temperature sensing unit utilizes PANI@PS micro-nanoparticles with an echinoid-like structure as the temperature-sensitive material, while in-situ photopolymerization technology ensures close contact between the thermal resistance electrodes and the temperature sensing layer, preventing contact resistance from being affected by pressure variations during temperature sensing. Additionally, based on the device's overall characteristics, a universal decoupling model was established for interference-free dual-mode temperature and pressure signal decoupling. The BDB electronic skin exhibits linear sensitivity (30.99 kPa−1) within a pressure range below 30 kPa and ultra-high sensitivity (0.29 K−1) across temperatures from room temperature to 80 °C. As shown in Fig. 1c, the vertical stacked hierarchical structure employed in this study demonstrates more balanced performance in sensitivity, signal acquisition convenience, decoupling, and anti-interference capabilities compared to single-device structures and planar integrated device architectures. Furthermore, it achieves superior integration relative to planar devices. The study also demonstrates the system's interference-free temperature perception capability by using a decision tree algorithm to real-time identify the temperature and water level in a cup. Leveraging the interference-free pressure sensing capability, convolutional neural networks (CNNs) were utilized to recognize the hardness and shape of objects grasped by the robotic hand. Meanwhile, the synchronous, interference-free cognitive capabilities of temperature and pressure enabled feedback control of the bio-inspired hand's contraction response.
Source: Sensor Expert Network