We propose a network architecture for electronic skin with an extensive sensor array—crucial for enabling robots to perceive their environment and interact effectively with humans. Fault tolerance is essential for electronic skins on robot exteriors. Although self-healing electronic skins targeting minor damages are studied using material-based approaches, substantial damages such as severe cuts necessitate re-establishing communication pathways, traditionally performed with high-functionality microprocessor sensor nodes. However, this method is costly, increases latency, and boosts power usage, limiting scalability for large, nuanced sensation-mimicking sensor arrays. Our proposed system features sensor nodes consisting of only a few dozen logic circuits, enabling them to autonomously reconstruct reading pathways. These nodes can adapt to topological changes within the sensor network caused by disconnections and reconnections. Testing confirms rapid reading times of only a few microseconds and power consumption of 1.88 μW/node at a 1 kHz sampling rate. This advancement significantly boosts robots’ collaborative potential with humans.

Laser scanners with mechanically driven mirrors have exhibited increasing potential for various applications, such as displays and laser radar. Resonant scanners are the predominantly used scanners; however, non-resonant scanners are required for applications where point-to-point driving is desirable. Because a non-resonant drive cannot amplify the drive angle owing to the resonance phenomenon, high values are difficult to achieve for the main performance metrics of the scanners: mirror area, drive angle, and operating frequency. In this paper, we present a two-axis scanner with a piezoelectric actuator made of a piezoelectric single-crystal Pb(In_1/2Nb_1/2)O₃-Pb(Mg_1/3Nb_2/3)O₃-PbTiO₃ as the actuation force source. The scanner contains a circular mirror with a diameter of 7 mm and achieves an average static mechanical deflection angle amplitude of 20.8° in two axes with a resonant frequency of 559 Hz. It is equipped with a transmission mechanism that can decouple each axis to achieve high linearity; in our study, the nonlinearity error was less than 1°.

A thermal micropressure sensor suitable for pressure measurements in the range from 7×10−3 to 1×105 Pa has been fabricated by forming a titanium (Ti) thin-film resistor on a floating nondoped silica glass membrane, with the sensing area being as small as 60 μm×60 μm. The sensor performance is raised by: (1) increasing the ratio of gaseous thermal conduction in the total thermal conduction by sensor structure design; (2) compensating the effect of ambient-temperature drift by using a reference resistor located close to the sensing element but directly on the silicon substrate; and (3) utilizing an optimized novel constant-bias Wheatstone bridge circuit. By choosing a proper bias voltage, which can be found by simple calculation, the circuit extracts information on gaseous thermal conduction from the directly measurable total heat loss of the heated sensing element. The sensor was enclosed in a metal package with a capacity of about 0.5 ml by projection welding and was successfully applied to monitoring the pressure in the minute space.

Accurate multi-axis inertial sensing is required for self-positioning estimation in automatic driving and robot posture control. In particular, a small bias drift is an important requirement for these applications. The bias drift is primarily caused by the external stress from the package. To reduce the bias drift in micro electro-mechanical systems (MEMS) sensors, a stress isolation suspension (SIS) structure inside the sensor chip is considered promising for miniaturization and cost reduction. To easily design an effective SIS, we propose a new design procedure based on the topology optimization method (TOM). The number of elements for the TOM in MEMS devices is often large owing to narrow lines and gaps such as release holes and comb-shaped electrodes, which increasing the computational cost of a TOM using an iterative algorithm. Before the TOM iterative calculation, we first identify the dominant external force mode affecting the bias drift using a single finite element analysis (FEA) with precise detailed geometry. Based on this, the TOM model is simplified. This combination of FEA and TOM allows a biasreducing topology-optimized SIS (T-SIS) structure to be designed with reduced computational cost. For validation, we applied the T-SIS design procedure to a capacitive accelerometer for z-axis bias drift reduction and compared its performance to accelerometers without T-SIS. The experimental results indicate that the T-SIS reduces the z-axis bias drift from ±811 mG to ±9.9 mG (temperature range: -30 °C to +70 °C), which is 1/80 of the bias drift of the sensor without T-SIS.

Electronic skin (e-skin) technology with high sensor distribution and versatility is required to develop robotic systems that exhibit the characteristics of living organisms. However, the scaling up of e-skins results in, issues such as the need for increased wiring, long readout time, and high power consumption. This study introduces a new circuit for a serial sensor network inspired by the signal propagation of neurons. The network comprises many sensor nodes chained together, wherein each node comprises only four logic elements for fast sub-microsecond readout and low power consumption (microwatts). Similar to neurons, each sensor node communicates only with the adjacent node, thereby avoiding an increase in the bus line load or a reduction in the communication bandwidth during scaling up. Additionally, various sensor products can be installed in a general-purpose manner.

Silicon-on-insulator (SOI) wafers are used in many micro-electromechanical system (MEMS) devices because of their stable mechanical properties. However, one of the disadvantages of using the SOI configuration is residual stress deformation; strong residual stresses in the buried-oxide layer deform the device and deteriorate its performance. This could prevent the development of high-precision sensors and actuators. In recent years, a new deformation mode caused by this residual stress has been reported, involving tilting of the suspended MEMS structure owing to local deformation of the anchor. However, methods to solve this problem have not yet been proposed. In this study, we propose a simple T-shaped support as a solution to the tilt deformation. We verified its effects by finite element analysis and experiments; the proposed structure was observed to successfully reduce the tip displacement of a SOI-based cantilever by one-fourth. In addition, we applied the proposed method to a parallel-plate accelerometer as a demonstration to confirm that the sensitivity variations of the device reduced from 10.8% to 6.8% using the proposed support structure. Thus, we believe that the proposed design can contribute to the development of extremely accurate MEMS sensors and optical devices.