Biomimetic Neuromorphic Sensory System via Electrolyte Gated Transistors.

Biomimetic neuromorphic sensing systems, inspired by the structure and function of biological neural networks, represent a major advancement in the field of sensing technology and artificial intelligence. This review paper focuses on the development and application of electrolyte gated transistors (EGTs) as the core components (synapses and neuros) of these neuromorphic systems. EGTs offer unique advantages, including low operating voltage, high transconductance, and biocompatibility, making them ideal for integrating with sensors, interfacing with biological tissues, and mimicking neural processes. Major advances in the use of EGTs for neuromorphic sensory applications such as tactile sensors, visual neuromorphic systems, chemical neuromorphic systems, and multimode neuromorphic systems are carefully discussed. Furthermore, the challenges and future directions of the field are explored, highlighting the potential of EGT-based biomimetic systems to revolutionize neuromorphic prosthetics, robotics, and human-machine interfaces. Through a comprehensive analysis of the latest research, this review is intended to provide a detailed understanding of the current status and future prospects of biomimetic neuromorphic sensory systems via EGT sensing and integrated technologies.

Bioinspired iontronic synapse fibers for ultralow-power multiplexing neuromorphic sensorimotor textiles.

Artificial neuromorphic devices can emulate dendric integration, axonal parallel transmission, along with superior energy efficiency in facilitating efficient information processing, offering enormous potential for wearable electronics. However, integrating such circuits into textiles to achieve biomimetic information perception, processing, and control motion feedback remains a formidable challenge. Here, we engineer a quasi-solid-state iontronic synapse fiber (ISF) comprising photoresponsive TiO2, ion storage Co-MoS2, and an ion transport layer. The resulting ISF achieves inherent short-term synaptic plasticity, femtojoule-range energy consumption, and the ability to transduce chemical/optical signals. Multiple ISFs are interwoven into a synthetic neural fabric, allowing the simultaneous propagation of distinct optical signals for transmitting parallel information. Importantly, IFSs with multiple input electrodes exhibit spatiotemporal information integration. As a proof of concept, a textile-based multiplexing neuromorphic sensorimotor system is constructed to connect synaptic fibers with artificial fiber muscles, enabling preneuronal sensing information integration, parallel transmission, and postneuronal information output to control the coordinated motor of fiber muscles. The proposed fiber system holds enormous promise in wearable electronics, soft robotics, and biomedical engineering.

Artificial organic afferent nerves enable closed-loop tactile feedback for intelligent robot.

The emulation of tactile sensory nerves to achieve advanced sensory functions in robotics with artificial intelligence is of great interest. However, such devices remain bulky and lack reliable competence to functionalize further synaptic devices with proprioceptive feedback. Here, we report an artificial organic afferent nerve with low operating bias (-0.6 V) achieved by integrating a pressure-activated organic electrochemical synaptic transistor and artificial mechanoreceptors. The dendritic integration function for neurorobotics is achieved to perceive directional movement of object, further reducing the control complexity by exploiting the distributed and parallel networks. An intelligent robot assembled with artificial afferent nerve, coupled with a closed-loop feedback program is demonstrated to rapidly implement slip recognition and prevention actions upon occurrence of object slippage. The spatiotemporal features of tactile patterns are well differentiated with a high recognition accuracy after processing spike-encoded signals with deep learning model. This work represents a breakthrough in mimicking synaptic behaviors, which is essential for next-generation intelligent neurorobotics and low-power biomimetic electronics.

A tactile sensing system capable of recognizing objects based on bioinspired self-sensing soft pneumatic actuator.

Tactile sensors play an important role when robots perform contact tasks, such as physical information collection, force or displacement control to avoid collision. For these manipulations, excessive contact may cause damage while poor contact cause information loss between the robotic end-effector and the objects. Inspired by skin structure and signal transmission method, this paper proposes a tactile sensing system based on the self-sensing soft pneumatic actuator (S-SPA) capable of providing tactile sensing capability for robots. Based on the adjustable height and compliance characteristics of the S-SPA, the contact process is safe and more tactile information can be collected. And to demonstrate the feasibility and advantage of this system, a robotic hand with S-SPAs could recognize different textures and stiffness of the objects by touching and pinching behaviours to collect physical information of the various objects under the positive work states of the S-SPA. The result shows the recognition accuracy of the fifteen texture plates reaches 99.4%, and the recognition accuracy of the four stiffness cuboids reaches 100%by training a KNN model. This safe and simple tactile sensing system with high recognition accuracies based on S-SPA shows great potential in robotic manipulations and is beneficial to applications in domestic and industrial fields.

Measurement of wing motion, deformation, and inertial forces of a biomimetic butterfly.

This paper introduces a method for measuring wing motion, deformation, and inertial forces in bio-inspired aircraft research using a camera motion capture system. The method involves placing markers on the wing surface and fitting rigid planes to determine the wing's spatial axis. This allows for describing the wing's rigid motion and obtaining deformation characteristics, such as deflection, twist angle, and gap distance of the forewing and hindwing. An image-based method is proposed for determining wing mass distribution, mass blocks, and mass points for inertial force measurement. The study addresses wing motion, deformation, and inertial force measurement in a real butterfly-like flapping wing vehicle and demonstrates the effectiveness of the approach. The results reveal that inertial forces play a negligible role in the generation of lift peaks and contribute minimal lift during the entire flapping cycle. Furthermore, a transitional phase between downstroke and upstroke is found in flexible wing motion, which has high lift production. This measurement approach offers a rapid and effective solution to experimental challenges in bio-inspired aircraft design and optimization.

Design of a bipedal robot for water running based on a six-linkage mechanism inspired by basilisk lizards.

Legged robots have received widespread attention in academia and engineering owing to their excellent terrain adaptability. However, most legged robots can only adapt to high-hardness environments instead of flexible environments. Expanding the motion range of legged robots to water is a promising but challenging work. Inspired by basilisk lizards which can run on water surfaces by feet, this paper proposes a bipedal robot for water running by hydrodynamics instead of buoyancy. According to the motion parameters of the basilisk lizard during water running, a single-degree of freedom bipedal mechanism is proposed to reproduce the motion trajectory of the feet of the basilisk lizard. Scale optimization is conducted by a particle swarm optimization algorithm to determine the geometrical parameters of the mechanism. The effects of motion frequency and foot area on mechanism performance are studied and the optimal solutions are determined by the maximum single-cycle lift impulse through numerical calculations. A bipedal water running robot prototype was fabricated, and the experimental results show that the prototype can generate enough support for the robot running on the water by providing a maximum lift of 2.4 times its weight (160 g) and reaching a horizontal forward speed range of 0.3-0.8 m s-1, compared with the basilisk lizard weighs 2-200 g, generates a lift impulse that is 111%-225% of its body weight, and moves at a speed of 1.3 ± 0.1 m s-1.

Biorealistic Neuronal Temperature-Sensitive Dynamics within Threshold Switching Memristors: Toward Neuromorphic Thermosensation.

Neuromorphic nanoelectronic devices that can emulate the temperature-sensitive dynamics of biological neurons are of great interest for bioinspired robotics and advanced applications such as in silico neuroscience. In this work, we demonstrate the biomimetic thermosensitive properties of two-terminal V3O5 memristive devices and showcase their similarity to the firing characteristics of thermosensitive biological neurons. The temperature-dependent electrical characteristics of V3O5-based memristors are used to understand the spiking response of a simple relaxation oscillator. The temperature-dependent dynamics of these oscillators are then compared with those of biological neurons through numerical simulations of a conductance-based neuron model, the Morris-Lecar neuron model. Finally, we demonstrate a robust neuromorphic thermosensation system inspired by biological thermoreceptors for bioinspired thermal perception and representation. These results not only demonstrate the biorealistic emulative potential of threshold-switching memristors but also establish V3O5 as a functional material for realizing solid-state neurons for neuromorphic computing and sensing applications.

Wall-climbing performance of gecko-inspired robot with soft feet and digits enhanced by gravity compensation.

Gravitational forces can induce deviations in body posture from desired configurations in multi-legged arboreal robot locomotion with low leg stiffness, affecting the contact angle between the swing leg's end-effector and the climbing surface during the gait cycle. The relationship between desired and actual foot positions is investigated here in a leg-stiffness-enhanced model under external forces, focusing on the challenge of unreliable end-effector attachment on climbing surfaces in such robots. Inspired by the difference in ceiling attachment postures of dead and living geckos, feedforward compensation of the stance phase legs is the key to solving this problem. A feedforward gravity compensation (FGC) strategy, complemented by leg coordination, is proposed to correct gravity-influenced body posture and improve adhesion stability by reducing body inclination. The efficacy of this strategy is validated using a quadrupedal climbing robot, EF-I, as the experimental platform. Experimental validation on an inverted surface (ceiling walking) highlights the benefits of the FGC strategy, demonstrating its role in enhancing stability and ensuring reliable end-effector attachment without external assistance. In the experiment, robots without FGC only completed 3 out of 10 trials, while robots with FGC achieved a 100% success rate in the same trials. The speed was substantially greater with FGC, achieving 9.2 mm s-1in the trot gait. This underscores the proposed potential of the FGC strategy in overcoming the challenges associated with inconsistent end-effector attachment in robots with low leg stiffness, thereby facilitating stable locomotion even at an inverted body attitude.

Skin-inspired, sensory robots for electronic implants.

Drawing inspiration from cohesive integration of skeletal muscles and sensory skins in vertebrate animals, we present a design strategy of soft robots, primarily consisting of an electronic skin (e-skin) and an artificial muscle. These robots integrate multifunctional sensing and on-demand actuation into a biocompatible platform using an in-situ solution-based method. They feature biomimetic designs that enable adaptive motions and stress-free contact with tissues, supported by a battery-free wireless module for untethered operation. Demonstrations range from a robotic cuff for detecting blood pressure, to a robotic gripper for tracking bladder volume, an ingestible robot for pH sensing and on-site drug delivery, and a robotic patch for quantifying cardiac function and delivering electrotherapy, highlighting the application versatilities and potentials of the bio-inspired soft robots. Our designs establish a universal strategy with a broad range of sensing and responsive materials, to form integrated soft robots for medical technology and beyond.

Microsaccade-inspired event camera for robotics.

Neuromorphic vision sensors or event cameras have made the visual perception of extremely low reaction time possible, opening new avenues for high-dynamic robotics applications. These event cameras' output is dependent on both motion and texture. However, the event camera fails to capture object edges that are parallel to the camera motion. This is a problem intrinsic to the sensor and therefore challenging to solve algorithmically. Human vision deals with perceptual fading using the active mechanism of small involuntary eye movements, the most prominent ones called microsaccades. By moving the eyes constantly and slightly during fixation, microsaccades can substantially maintain texture stability and persistence. Inspired by microsaccades, we designed an event-based perception system capable of simultaneously maintaining low reaction time and stable texture. In this design, a rotating wedge prism was mounted in front of the aperture of an event camera to redirect light and trigger events. The geometrical optics of the rotating wedge prism allows for algorithmic compensation of the additional rotational motion, resulting in a stable texture appearance and high informational output independent of external motion. The hardware device and software solution are integrated into a system, which we call artificial microsaccade-enhanced event camera (AMI-EV). Benchmark comparisons validated the superior data quality of AMI-EV recordings in scenarios where both standard cameras and event cameras fail to deliver. Various real-world experiments demonstrated the potential of the system to facilitate robotics perception both for low-level and high-level vision tasks.

Avian eye-inspired perovskite artificial vision system for foveated and multispectral imaging.

Avian eyes have deep central foveae as a result of extensive evolution. Deep foveae efficiently refract incident light, creating a magnified image of the target object and making it easier to track object motion. These features are essential for detecting and tracking remote objects in dynamic environments. Furthermore, avian eyes respond to a wide spectrum of light, including visible and ultraviolet light, allowing them to efficiently distinguish the target object from complex backgrounds. Despite notable advances in artificial vision systems that mimic animal vision, the exceptional object detection and targeting capabilities of avian eyes via foveated and multispectral imaging remain underexplored. Here, we present an artificial vision system that capitalizes on these aspects of avian vision. We introduce an artificial fovea and vertically stacked perovskite photodetector arrays whose designs were optimized by theoretical simulations for the demonstration of foveated and multispectral imaging. The artificial vision system successfully identifies colored and mixed-color objects and detects remote objects through foveated imaging. The potential for use in uncrewed aerial vehicles that need to detect, track, and recognize distant targets in dynamic environments is also discussed. Our avian eye-inspired perovskite artificial vision system marks a notable advance in bioinspired artificial visions.

Avian eye-inspired artificial vision takes a step forward.

Bioinspiration from avian eyes allows development of artificial vision systems with foveated and multispectral imaging.

Adaptivity of a leaf-inspired wind energy harvester with respect to wind speed and direction.

Environmental wind is a random phenomenon in both speed and direction, though it can be forecasted to some extent. An example of that is a gust which is an abrupt, but short-time change in wind speed and direction. Being a free and clean source for small-scale energy scavenging, attraction of wind is rapidly growing in the world of energy harvesters. In this paper, a leaf-like flapping wind energy harvester is introduced as the base structure in which a short-span airfoil is attached to the free end of a double-deck cantilever beam. A flap mechanism inspired by scales on sharks' skin and a tail mechanism inspired by birds' horizontal tail are proposed for integration to the base harvester to make it adaptive with respect to wind speed and direction, respectively. The use of the flap mechanism increases the leaf flapping frequency by +2.1 to +11.5 Hz at wind speeds of 1.5 to 6.0 m s-1. Therefore, since the output power of a vibrational harvester is a function of vibration frequency, a figure of merit or an efficiency parameter related to the output power will increase, as well. On the other hand, if there is a misalignment between the harvester's heading and wind direction due to change of the latter one, the harvesting performance deteriorates. Although the base harvester can realign in certain ranges of sideslip angle at each wind speed, when the tail mechanism is integrated into that, it broadens the range of realignable sideslip angles at all the investigated wind speeds by up to 80∘.

Legged robots beyond bioinspiration.

Advances in engineering enable wheeled-legged hybrid locomotion, an achievement not feasible in biological systems.

Nodes for modes: nodal honeycomb metamaterial enables a soft robot with multimodal locomotion.

Soft-bodied animals, such as worms and snakes, use many muscles in different ways to traverse unstructured environments and inspire tools for accessing confined spaces. They demonstrate versatility of locomotion which is essential for adaptation to changing terrain conditions. However, replicating such versatility in untethered soft-bodied robots with multimodal locomotion capabilities have been challenging due to complex fabrication processes and limitations of soft body structures to accommodate hardware such as actuators, batteries and circuit boards. Here, we present MetaCrawler, a 3D printed metamaterial soft robot designed for multimodal and omnidirectional locomotion. Our design approach facilitated an easy fabrication process through a discrete assembly of a modular nodal honeycomb lattice with soft and hard components. A crucial benefit of the nodal honeycomb architecture is the ability of its hard components, nodes, to accommodate a distributed actuation system, comprising servomotors, control circuits, and batteries. Enabled by this distributed actuation, MetaCrawler achieves five locomotion modes: peristalsis, sidewinding, sideways translation, turn-in-place, and anguilliform. Demonstrations showcase MetaCrawler's adaptability in confined channel navigation, vertical traversing, and maze exploration. This soft robotic system holds the potential to offer easy-to-fabricate and accessible solutions for multimodal locomotion in applications such as search and rescue, pipeline inspection, and space missions.

Design of an actuator with bionic claw hook-suction cup hybrid structure for soft robot.

To improve the adaptability of soft robots to the environment and achieve reliable attachment on various surfaces such as smooth and rough, this study draws inspiration from the collaborative attachment strategy of insects, cats, and other biological claw hooks and foot pads, and designs an actuator with a bionic claw hook-suction cup hybrid structure. The rigid biomimetic pop-up claw hook linkage mechanism is combined with a flexible suction cup of a 'foot pad' to achieve a synergistic adhesion effect between claw hook locking and suction cup adhesion through the deformation control of a soft pneumatic actuator. A pop-up claw hook linkage mechanism based on the principle of cat claw movement was designed, and the attachment mechanism of the biological claw hooks and footpads was analysed. An artificial muscle-spring-reinforced flexible pneumatic actuator (SRFPA) was developed and a kinematic model of the SRFPA was established and analysed using Abaqus. Finally, a prototype of the hybrid actuator was fabricated. The kinematic and mechanical performances of the SRFPA and entire actuator were characterised, and the attachment performance of the hybrid actuator to smooth and rough surfaces was tested. The results indicate that the proposed biomimetic claw hook-suction cup hybrid structure actuator is effective for various types of surface adhesion, object grasping, and robot walking. This study provides new insights for the design of highly adaptable robots and biomimetic attachment devices.

Dynamics of seaweed-inspired piezoelectric plates for energy harvesting from oscillatory cross flow.

Inspired by the vibrations of aquatic plants such as seaweed in the unsteady flow fields generated by free-surface waves, we investigate a novel device based on piezoelectric plates to harvest energy from oscillatory cross flows. Towards this end, numerical studies are conducted using a flow-structure-electric interaction model to understand the underlying physical mechanisms involved in the dynamics and energy harvesting performance of one or a pair of piezoelectric plates in an oscillatory cross flow. In a single-plate configuration, both periodic and irregular responses have been observed depending on parameters such as normalized plate stiffness and Keulegan-Carpenter number. Large power harvesting is achieved with the excitation of natural modes. Besides, when the time scale of the motion and the intrinsic time scale of the circuit are close to each other the power extraction is enhanced. In a two-plate configuration with tandem formation, the hydrodynamic interaction between the two plates can induce irregularity in the response. In terms of energy harvesting, two counteracting mechanisms have been identified, shielding and energy recovery. The shielding effect reduces plate motion and energy harvesting, whereas with the energy recovery effect one plate is able to recovery energy from the wake of another for performance enhancement. The competition between these mechanisms leads to constructive or destructive interactions between the two plates. These results suggest that for better performance the system should be excited at its natural period, which should be close to the intrinsic time scale of the circuit. Moreover, using a pair of plates in a tandem formation can further improve the energy harvesting capacity when conditions for constructive interaction are satisfied.

A toe-inspired rigid-flexible coupling wheel design method for improving the terrain adaptability of a sewer robot.

The human toe, characterized by its rigid-flexible structure comprising hard bones and flexible joints, facilitates adaptive and stable movement across varied terrains. In this paper, we utilized a motion capture system to study the adaptive adjustments of toe joints when encountering obstacles. Inspired by the mechanics of toe joints, we proposed a novel design method for a rigid-flexible coupled wheel. The wheel comprises multiple elements: a rigid skeleton, supporting toes, connecting shafts, torsion springs, soft tendons, and damping pads. The torsion springs connect the rigid frame to the supporting toes, enabling them to adapt to uneven terrains and pipes with different diameters. The design was validated through kinematic and dynamic modeling, rigid-flexible coupled dynamics simulation, and stress analysis. Different stiffness coefficients of torsion springs were compared for optimal wheel design. Then, the wheel was applied to a sewer robot, and its performance was evaluated and compared with a pneumatic rubber tire in various experiments, including movement on flat surfaces, overcoming small obstacles, adaptability tests in different terrains, and active driving force tests in dry and wet pipelines. The results prove that the designed wheel showed better stability and anti-slip properties than conventional tires, making it suitable for diverse applications such as pipeline robots, desert vehicles, and lunar rovers.

Visualized in-sensor computing.

In artificial nervous systems, conductivity changes indicate synaptic weight updates, but they provide limited information compared to living organisms. We present the pioneering design and production of an electrochromic neuromorphic transistor employing color updates to represent synaptic weight for in-sensor computing. Here, we engineer a specialized mechanism for adaptively regulating ion doping through an ion-exchange membrane, enabling precise control over color-coded synaptic weight, an unprecedented achievement. The electrochromic neuromorphic transistor not only enhances electrochromatic capabilities for hardware coding but also establishes a visualized pattern-recognition network. Integrating the electrochromic neuromorphic transistor with an artificial whisker, we simulate a bionic reflex system inspired by the longicorn beetle, achieving real-time visualization of signal flow within the reflex arc in response to environmental stimuli. This research holds promise in extending the biomimetic coding paradigm and advancing the development of bio-hybrid interfaces, particularly in incorporating color-based expressions.

A Retina-Inspired Optoelectronic Synapse Using Quantum Dots for Neuromorphic Photostimulation of Neurons.

Neuromorphic electronics, inspired by the functions of neurons, have the potential to enable biomimetic communication with cells. Such systems require operation in aqueous environments, generation of sufficient levels of ionic currents for neurostimulation, and plasticity. However, their implementation requires a combination of separate devices, such as sensors, organic synaptic transistors, and stimulation electrodes. Here, a compact neuromorphic synapse that combines photodetection, memory, and neurostimulation functionalities all-in-one is presented. The artificial photoreception is facilitated by a photovoltaic device based on cell-interfacing InP/ZnS quantum dots, which induces photo-faradaic charge-transfer mediated plasticity. The device sends excitatory post-synaptic currents exhibiting paired-pulse facilitation and post-tetanic potentiation to the hippocampal neurons via the biohybrid synapse. The electrophysiological recordings indicate modulation of the probability of action potential firing due to biomimetic temporal summation of excitatory post-synaptic currents. These results pave the way for the development of novel bioinspired neuroprosthetics and soft robotics, and highlight the potential of quantum dots for achieving versatile neuromorphic functionality in aqueous environments.