FOCERS: An Ultrasensitive and Robust Soft Optical 3D Tactile Sensor

Soft optical sensors, characterized by excellent stability, strong anti-interference ability, and rapid response, are particularly suitable for exploring unknown environments. However, the low sensitivity and large size of optical tactile sensors have limited their widespread application. This study presents an ultrasensitive, highly linear, and highly robust three-dimensional (3D) tactile sensor based on a Foldable Optical Circuit Embedded in Rigid-Soft-coupled (FOCERS) structure. This sensor exhibits a high sensitivity of 1228.7 kPa-1 under normal pressure of 5 kPa, a super high sensitivity of 7399.5 kPa-1 under a sheer pressure of 1.5 kPa, and a fast response time of 5 ms. Under normal pressure conditions, the sensors exhibited high linearity performance across the entire sensing range, with linearity reaching up to 95.3%. The rigid-soft-coupled structure enhances the robustness and overload resistance of the sensor (withstanding 50 times the sensing range). Demonstrations show that the FOCERS structure can detect minute pressure variations (induced by sesame seeds) and withstand extreme pressures (such as being run over by a car). Furthermore, we designed a joystick based on FOCERS for force detection in human-machine interactions. This study provides a new structure for optical sensors to increase both sensitivity and robustness, and also provides a convenient way to fabricate 3D tactile sensors.

Multi-axis robotic forceps with decoupled pneumatic actuation and force sensing for cochlear implantation

Delicate manual microsurgeries rely on sufficient hands-on experience for safe manipulations. Automated surgical devices can enhance the effectiveness, but developing high-resolution, multi-axis force-sensing devices for micro operations remains challenging. In this study, a 6-axis force-sensing pneumatic forceps with a serial-parallel robotic platform for cochlear implantation is developed. The forceps features a curved body shape embedded with parallel and inclined fiber Bragg grating sensors for 6-axis force sensing, and a pneumatic gripper with decoupled actuation is located at its end for actively grasping and releasing the electrode array. The robotic platform comprises a customized spherical parallel mechanism and a robotic arm, which can provide independent 3-DOF rotations and 3-DOF translations. The feasibility of the developed robotic forceps is validated through cadaveric studies on a temporal bone and a human cadaveric head. In summary, the robotic forceps provides a decoupled mechanism for pneumatic actuation and force sensing, further demonstrating its potential for force interaction and stable operation during robotic microsurgery.

Digital channel-enabled distributed force decoding via small datasets for hand-centric interactions

Tactile interfaces are essential for enhancing human-machine interactions, yet achieving large-scale, precise distributed force sensing remains challenging due to signal coupling and inefficient data processing. Inspired by the spiral structure of Aloe polyphylla and the processing principles of neuronal systems, this study presents a digital channel-enabled distributed force decoding strategy, resulting in a phygital tactile sensing system named PhyTac. This innovative system effectively prevents marker overlap and accurately identifies multipoint stimuli up to 368 regions from coupled signals. By integrating physics into model training, we reduce the dataset size to just 45 kilobytes, surpassing conventional methods that typically exceed 1 gigabyte. Results demonstrate PhyTac's impressive fidelity of 97.7% across a sensing range of 0.5 to 25 newtons, enabling diverse applications in medical evaluation, sports training, virtual reality, and robotics. This research not only enhances our understanding of hand-centric actions but also highlights the convergence of physical and digital realms, paving the way for advancements in AI-based sensor technologies.

JamTac: A Tactile Jamming Gripper for Searching and Grasping in Low-Visibility Environments

Humans can feel and grasp efficiently in the dark through tactile feedback, whereas it is still a challenging task for robots. In this research, we create a novel soft gripper named JamTac, which has high-resolution tactile perception, a large detection surface, and integrated sensing-grasping capability that can search and grasp in low-visibility environments. The gripper combines granular jamming and visuotactile perception technologies. Using the principle of refractive index matching, a refraction-free liquid-particle rationing scheme is developed, which makes the gripper itself to be an excellent tactile sensor without breaking its original grasping capability. We simultaneously acquire color and depth information inside the gripper, making it possible to sense the shape, texture, hardness, and contact force with high resolution. Experimental results demonstrate that JamTac can be a promising tool to search and grasp in situations when vision is not available.

Ferroelectret nanogenerators for the development of bioengineering systems

Bioengineering devices and systems will become a practical and versatile technology in society when sustainability issues, primarily pertaining to their efficiency, sustainability, and human-machine interaction, are fully addressed. It has become evident that technological paths should not rely on a single operation mechanism but instead on holistic methodologies that integrate different phenomena and approaches with complementary advantages. As an intriguing invention, the ferroelectret nanogenerator (FENG) has emerged with promising potential in various fields of bioengineering. Utilizing the changes in the engineered macro-scale electric dipoles to create displacement current (and vice versa), FENGs have been demonstrated to be a compelling strategy for bidirectional conversion of energy between the electrical and mechanical domains. Here we provide a comprehensive overview of the latest advancements in integrating FENGs in bioengineering systems, focusing on the applications with the most potential and the underlying current constraints.

A biomimetic elastomeric robot skin using electrical impedance and acoustic tomography for tactile sensing

Human skin perceives physical stimuli applied to the body and mitigates the risk of physical interaction through its soft and resilient mechanical properties. Social robots would benefit from whole-body robotic skin (or tactile sensors) resembling human skin in realizing a safe, intuitive, and contact-rich human-robot interaction. However, existing soft tactile sensors show several drawbacks (complex structure, poor scalability, and fragility), which limit their application in whole-body robotic skin. Here, we introduce biomimetic robotic skin based on hydrogel-elastomer hybrids and tomographic imaging. The developed skin consists of a tough hydrogel and a silicone elastomer forming a skin-inspired multilayer structure, achieving sufficient softness and resilience for protection. The sensor structure can also be easily repaired with adhesives even after severe damage (incision). For multimodal tactile sensation, electrodes and microphones are deployed in the sensor structure to measure local resistance changes and vibration due to touch. The ionic hydrogel layer is deformed owing to an external force, and the resulting local conductivity changes are measured via electrodes. The microphones also detect the vibration generated from touch to determine the location and type of dynamic tactile stimuli. The measurement data are then converted into multimodal tactile information through tomographic imaging and deep neural networks. We further implement a sensorized cosmetic prosthesis, demonstrating that our design could be used to implement deformable or complex-shaped robotic skin.

A soft thumb-sized vision-based sensor with accurate all-round force perception

Vision-based haptic sensors have emerged as a promising approach to robotic touch due to affordable high-resolution cameras and successful computer vision techniques; however, their physical design and the information they provide do not yet meet the requirements of real applications. We present a robust, soft, low-cost, vision-based, thumb-sized three-dimensional haptic sensor named Insight, which continually provides a directional force-distribution map over its entire conical sensing surface. Constructed around an internal monocular camera, the sensor has only a single layer of elastomer over-moulded on a stiff frame to guarantee sensitivity, robustness and soft contact. Furthermore, Insight uniquely combines photometric stereo and structured light using a collimator to detect the three-dimensional deformation of its easily replaceable flexible outer shell. The force information is inferred by a deep neural network that maps images to the spatial distribution of three-dimensional contact force (normal and shear). Insight has an overall spatial resolution of 0.4 mm, a force magnitude accuracy of around 0.03 N and a force direction accuracy of around five degrees over a range of 0.03–2 N for numerous distinct contacts with varying contact area. The presented hardware and software design concepts can be transferred to a wide variety of robot parts.