MEMS-Based Tactile Sensors: Materials, Processes and Applications in Robotics

Fabrication and Electrical Characterization of Low-Temperature Polysilicon Films for Sensor Applications

The development of low-temperature piezoresistive materials provides compatibility with standard silicon-based MEMS fabrication processes. Additionally, it enables the use of such material in flexible substrates, thereby expanding the potential for various device applications. This work demonstrates, for the first time, the fabrication of a 200 nm polycrystalline silicon thin film through a metal-induced crystallization process mediated by an AlSiCu alloy at temperatures as low as 450 °C on top of silicon and polyimide (PI) substrates. The resulting polycrystalline film structure exhibits crystallites with a size of approximately 58 nm, forming polysilicon (poly-Si) grains with diameters between 1-3 µm for Si substrates and 3-7 µm for flexible PI substrates. The mechanical and electrical properties of the poly-Si were experimentally conducted using microfabricated test structures containing piezoresistors formed by poly-Si with different dimensions. The poly-Si material reveals a longitudinal gauge factor (GF) of 12.31 and a transversal GF of -4.90, evaluated using a four-point bending setup. Additionally, the material has a linear temperature coefficient of resistance (TCR) of -2471 ppm/°C. These results illustrate the potential of using this low-temperature film for pressure, force, or temperature sensors. The developed film also demonstrated sensitivity to light, indicating that the developed material can also be explored in photo-sensitive applications.

Leveraging imitation learning in agricultural robotics: a comprehensive survey and comparative analysis

Imitation learning (IL), a burgeoning frontier in machine learning, holds immense promise across diverse domains. In recent years, its integration into robotics has sparked significant interest, offering substantial advancements in autonomous control processes. This paper presents an exhaustive insight focusing on the implementation of imitation learning techniques in agricultural robotics. The survey rigorously examines varied research endeavors utilizing imitation learning to address pivotal agricultural challenges. Methodologically, this survey comprehensively investigates multifaceted aspects of imitation learning applications in agricultural robotics. The survey encompasses the identification of agricultural tasks that can potentially be addressed through imitation learning, detailed analysis of specific models and frameworks, and a thorough assessment of performance metrics employed in the surveyed studies. Additionally, it includes a comparative analysis between imitation learning techniques and conventional control methodologies in the realm of robotics. The findings derived from this survey unveil profound insights into the applications of imitation learning in agricultural robotics. These methods are highlighted for their potential to significantly improve task execution in dynamic and high-dimensional action spaces prevalent in agricultural settings, such as precision farming. Despite promising advancements, the survey discusses considerable challenges in data quality, environmental variability, and computational constraints that IL must overcome. The survey also addresses the ethical and social implications of implementing such technologies, emphasizing the need for robust policy frameworks to manage the societal impacts of automation. These findings hold substantial implications, showcasing the potential of imitation learning to revolutionize processes in agricultural robotics. This research significantly contributes to envisioning innovative applications and tools within the agricultural robotics domain, promising heightened productivity and efficiency in robotic agricultural systems. It underscores the potential for remarkable enhancements in various agricultural processes, signaling a transformative trajectory for the sector, particularly in the realm of robotics and autonomous systems.

Inductive Paper-Based Flexible Contact Force Sensor Utilizing Natural Micro-Nanostructures of Paper: Simplicity, Economy, and Eco-Friendliness

Inductive contact force sensors, known for their high precision and anti-interference capabilities, hold significant potential applications in fields such as wearable and medical monitoring devices. Most of the current research on inductive contact force sensors employed novel nanomaterials as sensitive elements to enhance their sensitivity and other performance characteristics. However, sensors developed through such methods typically involve complex preparation processes, high costs, and difficulty in biodegradation, which limit their further development. This article introduces a new flexible inductive contact force sensor using paper as a sensitive element. Paper inherently possesses micro- and nanostructures on its surface and interior, enabling it to sensitively convert changes in contact force into changes in displacement, making it suitable for use as the sensor's sensitive element. Additionally, the advantages of paper also include its great flexibility, low cost, wide availability, and biodegradability. Performance testing on this flexible sensor showed good repeatability, hysteresis, sensitivity, and consistency. When used in experiments for monitoring human motion and respiration, this sensor also exhibited great detection performance. The proposed inductive paper-based flexible contact force sensor, with its simple structure, easy manufacturing process, cost-effectiveness, eco-friendliness, and good sensing performance, provides new insights into research for contact force sensors.

Haptic Sensing and Feedback Techniques toward Virtual Reality

Haptic interactions between human and machines are essential for information acquisition and object manipulation. In virtual reality (VR) system, the haptic sensing device can gather information to construct virtual elements, while the haptic feedback part can transfer feedbacks to human with virtual tactile sensation. Therefore, exploring high-performance haptic sensing and feedback interface imparts closed-loop haptic interaction to VR system. This review summarizes state-of-the-art VR-related haptic sensing and feedback techniques based on the hardware parts. For the haptic sensor, we focus on mechanism scope (piezoresistive, capacitive, piezoelectric, and triboelectric) and introduce force sensor, gesture translation, and touch identification in the functional view. In terms of the haptic feedbacks, methodologies including mechanical, electrical, and elastic actuators are surveyed. In addition, the interactive application of virtual control, immersive entertainment, and medical rehabilitation is also summarized. The challenges of virtual haptic interactions are given including the accuracy, durability, and technical conflicts of the sensing devices, bottlenecks of various feedbacks, as well as the closed-loop interaction system. Besides, the prospects are outlined in artificial intelligence of things, wise information technology of medicine, and multimedia VR areas.

A polymeric piezoelectric MEMS accelerometer with high sensitivity, low noise density, and an innovative manufacturing approach

The piezoelectric coupling principle is widely used (along with capacitive coupling and piezoresistive coupling) for MEMS accelerometers. Piezoelectric MEMS accelerometers are used primarily for vibration monitoring. Polymer piezoelectric MEMS accelerometers offer the merits of heavy-metal-free structure material and simple microfabrication flow. More importantly, polymeric piezoelectric MEMS accelerometers may be the basis of novel applications, such as fully organic inertial sensing microsystems using polymer sensors and organic integrated circuits. This paper presents a novel polymer piezoelectric MEMS accelerometer design using PVDF films. A simple and rapid microfabrication flow based on laser micromachining of thin films and 3D stereolithography was developed to fabricate three samples of this design. During proof-of-concept experiments, the design achieved a sensitivity of 21.82 pC/g (equivalent open-circuit voltage sensitivity: 126.32 mV/g), a 5% flat band of 58.5 Hz, and a noise density of 6.02 µg/√Hz. Thus, this design rivals state-of-the-art PZT-based counterparts in charge sensitivity and noise density, and it surpasses the performance capabilities of several commercial MEMS accelerometers. Moreover, this design has a 10-times smaller device area and a 4-times larger flat band than previous state-of-the-art organic piezoelectric MEMS accelerometers. These experimentally validated performance metrics demonstrate the promising application potential of the polymeric piezoelectric MEMS accelerometer design presented in this article.

A 3D Composited Flexible Sensor Based on Percolative Nanoparticle Arrays to Discriminate Coupled Pressure and Strain

Flexible mechanical sensors based on nanomaterials operate on a deformation-response mechanism, making it challenging to discern different types of mechanical stimuli such as pressure and strain. Therefore, these sensors are susceptible to significant mechanical interference. Here, we introduce a multifunctional flexible sensor capable of discriminating coupled pressure and strain without cross-interference. Our design involves an elastic cantilever fixed on the pillar of the flexible main substrate, creating a three-dimensional (3D) substrate, and two percolative nanoparticle (NP) arrays are deposited on the cantilever and main substrate, respectively, as the sensing materials. The 3D flexible substrate could confine pressure/strain loading exclusively on the cantilever or main substrate, resulting in independent responses of the two nanoparticle arrays with no cross-interference. Benefitting from the quantum transport in nanoparticle arrays, our sensors demonstrate an exceptional sensitivity, enabling discrimination of subtle strains down to 1.34 × 10^-4. Furthermore, the suspended cantilever with one movable end can enhance the pressure perception of the NP array, exhibiting a high sensitivity of -0.223 kPa^-1 and an ultrahigh resolution of 4.24 Pa. This flexible sensor with multifunctional design will provide inspiration for the development of flexible mechanical sensors and the advancement of decoupling strategies.

Measures of Maximal Tactile Pressures during a Sustained Grasp Task Using a TactArray Device Have Satisfactory Reliability and Concurrent Validity in People with Stroke

Sensor-based devices can record pressure or force over time during grasping and therefore offer a more comprehensive approach to quantifying grip strength during sustained contractions. The objectives of this study were to investigate the reliability and concurrent validity of measures of maximal tactile pressures and forces during a sustained grasp task using a TactArray device in people with stroke. Participants with stroke (n = 11) performed three trials of sustained maximal grasp over 8 s. Both hands were tested in within- and between-day sessions, with and without vision. Measures of maximal tactile pressures and forces were measured for the complete (8 s) grasp duration and plateau phase (5 s). Tactile measures are reported using the highest value among three trials, the mean of two trials, and the mean of three trials. Reliability was determined using changes in mean, coefficients of variation, and intraclass correlation coefficients (ICCs). Pearson correlation coefficients were used to evaluate concurrent validity. This study found that measures of reliability assessed by changes in means were good, coefficients of variation were good to acceptable, and ICCs were very good for maximal tactile pressures using the average pressure of the mean of three trials over 8 s in the affected hand with and without vision for within-day sessions and without vision for between-day sessions. In the less affected hand, changes in mean were very good, coefficients of variations were acceptable, and ICCs were good to very good for maximal tactile pressures using the average pressure of the mean of three trials over 8 s and 5 s, respectively, in between-day sessions with and without vision. Maximal tactile pressures had moderate correlations with grip strength. The TactArray device demonstrates satisfactory reliability and concurrent validity for measures of maximal tactile pressures in people with stroke.