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Innovative human–machine interfaces (HMIs) have attracted increasing attention in the field of system control and assistive devices for disabled people. Conventional HMIs that are designed based on the interaction of physical movements or language communication are not effective or appliable to severely disabled users. Here, a breath‐driven triboelectric sensor is reported consisting of a soft fixator and two circular‐shaped triboelectric nanogenerators (TENGs) for self‐powered respiratory monitoring and smart system control. The sensor device is capable of effectively detecting the breath variation and generates responsive electrical signals based on different breath patterns without affecting the normal respiration. A breathing‐driven HMI system is demonstrated for severely disabled people to control electrical household appliances and shows an intelligent respiration monitoring system for emergence alarm. The new system provides the advantages of high sensitivity, good stability, low cost, and ease of use. This work will not only expand the development of the TENGs in self‐powered sensors, but also opens a new avenue to develop assistive devices for disabled people through innovation of advanced HMIs.

 

Electronic textiles (e‐textiles) that combine the wearing comfort of textiles and the functionality of soft electronics are highly demanded in wearable applications. However, fabricating robust high‐performance stretchable e‐textiles with good abrasion resistance and high‐resolution aesthetic patterns for high‐throughput manufacturing and practical applications remains challenging. Herein, the authors report a new multifunctional e‐textile fabricated via screen printing of the water‐based silver fractal dendrites conductive ink. The as‐fabricated e‐textiles spray‐coated with the invisible waterproofing agent exhibit superior flexibility, water resistance, wearing comfort, air permeability, and abrasion resistance, achieving a low sheet resistance of 0.088 Ω sq⁻¹, high stretchability of up to 154%, and excellent dynamic stability for over 1000 cyclic testing (ε = 100%). The printed e‐textiles can be explored as strain sensors and ultralow voltage‐driven Joule heaters driven for personalized thermal management. They finally demonstrate an integrated aesthetic smart clothing made of their multifunctional e‐textiles for human motion detection and body‐temperature management. The printed e‐textiles provide new opportunities for developing novel wearable electronics and smart clothing for future commercial applications.

 

Soft robots have attracted great attention in the past decades owing to their unique flexibility and adaptability for accomplishing tasks via simple control strategies, as well as their inherent safety for interactions with humans and environments. Here, a soft robotic manipulation system capable of stiffness variation and dexterous operations through a remotely controlled manner is reported. The smart manipulation system consists of a soft omnidirectional arm, a dexterous multimaterial gripper, and a self‐powered human–machine interface (HMI) for teleoperation. The cable‐driven soft arm is made of soft elastomers and embedded with low melting point alloy as a stiffness‐tuning mechanism. The self‐powered HMI patches are designed based on the triboelectric nanogenerator that utilizes a sliding mode of tribo‐layers made of copper and polytetrafluoroethylene. The novel soft manipulation system has great potential for soft and remote manipulation and human machine interactions in a variety of applications from elderly care to surgical operation to agriculture harvesting.

 

Soil sensors and plant wearables play a critical role in smart and precision agriculture via monitoring real‐time physical and chemical signals in the soil, such as temperature, moisture, pH, and pollutants and providing key information to optimize crop growth circumstances, fight against biotic and abiotic stresses, and enhance crop yields. Herein, the recent advances of the important soil sensors in agricultural applications, including temperature sensors, moisture sensors, organic matter compounds sensors, pH sensors, insect/pest sensors, and soil pollutant sensors are reviewed. Major sensing technologies, designs, performance, and pros and cons of each sensor category are highlighted. Emerging technologies such as plant wearables and wireless sensor networks are also discussed in terms of their applications in precision agriculture. The research directions and challenges of soil sensors and intelligent agriculture are finally presented.

 

Stretchable supercapacitors (SCs) have attracted significant attention in developing power‐independent stretchable electronic systems due to their intrinsic energy storage function and unique mechanical properties. Most current SCs are generally limited by their low stretchability, complicated fabrication process, and insufficient performance and robustness. This study presents a facile method to fabricate arbitrary‐shaped stretchable electrodes via 4D printing of conductive composite from reduced graphene oxide, carbon nanotube, and poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate. The electrode patterns of an arbitrary shape can be deposited onto prestretched substrates by aerosol‐jet printing, then self‐organized origami (ridge) patterns are generated after releasing the substrates from holding stretchers due to the mismatched strains. The stretchable electrodes demonstrate superior mechanical robustness and stretchability without sacrificing its outstanding electrochemical performance. The symmetric SC prototype possesses a gravimetric capacitance of ≈21.7 F g⁻¹at a current density of 0.5 A g⁻¹and a capacitance retention of ≈85.8% from 0.5 to 5 A g⁻¹. A SC array with arbitrary‐shaped electrodes is also fabricated and connected in series to power light‐emitting diode patterns for large‐scale applications. The proposed method paves avenues for scalable manufacturing of future energy‐storage devices with controlled extensibility and high electrochemical performance.

 

Using the context of human-supervised object collection tasks, we explore policies for a robot to seek assistance from a human supervisor and avoid loss of human trust in the robot. We consider a human-robot interaction scenario in which a mobile manipulator chooses to collect objects either autonomously or through human assistance; while the human supervisor monitors the robot’s operation, assists when asked, or intervenes if the human perceives that the robot may not accomplish its goal. We design an optimal assistance-seeking policy for the robot using a Partially Observable Markov Decision Process (POMDP) setting in which human trust is a hidden state and the objective is to maximize collaborative performance. We conduct two sets of human-robot interaction experiments. The data from the first set of experiments is used to estimate POMDP parameters, which are used to compute an optimal assistance-seeking policy that is used in the second experiment. For most participants, the estimated POMDP reveals that humans are more likely to intervene when their trust is low and the robot is performing a high-complexity task; and that the robot asking for assistance in high-complexity tasks can increase human trust in the robot. Our experimental results show that the proposed trust-aware policy yields superior performance compared with an optimal trust-agnostic policy. 

We propose Deterministic Sequencing of Exploration and Exploitation (DSEE) algorithm with interleaving exploration and exploitation epochs for model-based RL problems that aim to simultaneously learn the system model, i.e., a Markov decision process (MDP), and the associated optimal policy. During exploration, DSEE explores the environment and updates the estimates for expected reward and transition probabilities. During exploitation, the latest estimates of the expected reward and transition probabilities are used to obtain a robust policy with high probability. We design the lengths of the exploration and exploitation epochs such that the cumulative regret grows as a sub-linear function of time.