Search Results (9)

Human–robot collaboration stands as one of the research frontiers in industrial applications due to the possibility for human operators to be supported by robots in carrying out their tasks in a shared workspace. However, advances in this field can be slowed down by the lack of standards regarding the safety and ergonomics of such applications. This article aims at reducing this gap by presenting an adaptation of the standard ISO 11228-3 for the ergonomic evaluation of hand-guiding applications through the OCRA index. This innovative methodology is innovatively applied to a drilling application in which a human operator hand-guides a collaborative robotic system consisting of a Franka Emika Panda robot, a force/torque sensor and an IMU suit to track the motion of the operator’s body. The SaRAH app, a MATLAB 2020a-based software tool developed on purpose, implements the ergonomic assessment procedure, allowing the proper redesign of the working shift (offline mode) or providing the worker suggestions to improve his/her behavior (online mode) so as to reduce the ergonomic risk. Full article

With the long-term water-flooding development of the reservoir, the non-homogeneity of the formation is increasing and the reservoir environment is deteriorating; the microspheres used for deep plugging have shown disadvantages, such as poor temperature and salt resistance and faster expansion. In this study, a polymeric microsphere was synthesized that is resistant to high temperature and high salt and can achieve slow expansion and slow release for deep migration. P(AA-AM-SA)@TiO₂ polymer gel/inorganic nanoparticle microspheres were prepared by reversed-phase microemulsion polymerization using acrylamide (AM) and acrylic acid (AA) as monomers, 3-methacryloxypropyltrimethoxysilane (KH-570)-modified TiO₂ as the inorganic core, and sodium alginate (SA) as a temperature-sensitive coating material. Through single-factor analysis of the polymerization process, the optimal synthesis conditions were determined as follows: the oil(Cyclohexane)-water volume ratio was 8:5, the emulsifier mass ratio (Span-80:Tween-80) was 3:1 (10 wt% of the total system amount), the stirring speed was 400 r/min, the reaction temperature was 60 °C, and the initiator (ammonium persulfate and sodium bisulfite) dosage was 0.6 wt%. The size of the dried polymer gel/inorganic nanoparticle microspheres prepared by the optimized synthesis conditions was 10~40 μm with uniform particle size. The observation of P(AA-AM-SA)@TiO₂ microspheres reveals that the Ca elements are uniformly distributed on the microspheres, and FT-IR indicates that the synthesized product is the target product. TGA shows that the polymer gel/inorganic nanoparticle microspheres have better thermal stability after the addition of TiO₂, with a larger mass loss at 390 °C, which can adapt to the medium-high permeability reservoir environment. The thermal and aqueous salinity resistance of the P(AA-AM-SA)@TiO₂ microspheres was tested, and the cracking temperature of P(AA-AM-SA)@TiO₂ microsphere temperature-sensitive material was 90 °C. It still has favorable water absorption and swelling performance under the sodium salt concentration of 2.5 × 10⁴ mg/L and can tolerate calcium salt up to 2.0 × 10⁴ mg/L. Plugging Performance Test results show that the microspheres have good injectability between the permeability of 1.23 and 2.35 μm² and good plugging effect near the permeability of 2.20 μm². At high temperature and high salinity, P(AA-AM-SA)@TiO₂ microspheres have a remarkable effect on profile control and water shutoff, the plugging rate reaches 95.3%, and the oil recovery rate is increased by 12.89% compared with water flooding, achieving the effect of slow swelling and slow release. Full article

The electrochemical paradigm of a supercapacitor (SC) is effective for investigating cutting-edge deformable and haptic materials made of magnetic compound fluid (MCF) rubber in order to advance the production of bio-inspired sensors as artificial haptic sensors mimicking human tissues. In the present study, we measure the cyclic voltammetry (CV) profiles and electric properties with electrochemical impedance spectroscopy (EIS) to morphologically evaluate the intrinsic structure of MCF rubber containing fillers and agents. In addition, the electrochemical mechanisms of molecule and particle behavior are theorized using the SC physical framework. The solid-doped fillers in the MCF rubber characterized the behavior of the electrical double-layer capacitor (EDLC). Meanwhile, the liquid agents showed the characteristics of a pseudocapacitor (PC) due to the redox response among the molecules and particles. The potential responses to extraneous stimuli relevant to the EIS properties, categorized as slow adaption (SA), fast adaption (FA), and other type (OT), were also analyzed in terms of the sensory response of the bio-inspired sensor. The categories were based on how the response was induced from the EIS properties. By controlling the EIS properties with different types of doping agents, sensors with various sensory responses become feasible. Full article

In order to advance the development of sensors fabricated with monofunctional sensation systems capable of a versatile response to tactile, thermal, gustatory, olfactory, and auditory sensations, mechanoreceptors fabricated as a single platform with an electric circuit require investigation. In addition, it is essential to resolve the complicated structure of the sensor. In order to realize the single platform, our proposed hybrid fluid (HF) rubber mechanoreceptors of free nerve endings, Merkel cells, Krause end bulbs, Meissner corpuscles, Ruffini endings, and Pacinian corpuscles mimicking the bio-inspired five senses are useful enough to facilitate the fabrication process for the resolution of the complicated structure. This study used electrochemical impedance spectroscopy (EIS) to elucidate the intrinsic structure of the single platform and the physical mechanisms of the firing rate such as slow adaption (SA) and fast adaption (FA), which were induced from the structure and involved the capacitance, inductance, reactance, etc. of the HF rubber mechanoreceptors. In addition, the relations among the firing rates of the various sensations were clarified. The adaption of the firing rate in the thermal sensation is the opposite of that in the tactile sensation. The firing rates in the gustation, olfaction, and auditory sensations at frequencies of less than 1 kHz have the same adaption as in the tactile sensation. The present findings are useful not only in the field of neurophysiology, to research the biochemical reactions of neurons and brain perceptions of stimuli, but also in the field of sensors, to advance salient developments in sensors mimicking bio-inspired sensations. Full article

Traditional trajectory-planning methods are unable to achieve time optimization, resulting in slow response times to unexpected situations. To address this issue and improve the smoothness of joint trajectories and the movement time of quadruped robots, we propose a trajectory-planning method based on time optimization. This approach improves the whale optimization algorithm with simulated annealing (IWOA-SA) together with adaptive weights to prevent the whale optimization algorithm (WOA) from falling into local optima and to balance its exploration and exploitation abilities. We also use Markov chains of stochastic process theory to analyze the global convergence of the proposed algorithm. The results show that our optimization algorithm has stronger optimization ability and stability when compared to six representative algorithms using six different test function suites in multiple dimensions. Additionally, the proposed optimization algorithm consistently constrains the angular velocity of each joint within the range of kinematic constraints and reduces joint running time by approximately 6.25%, which indicates the effectiveness of this algorithm. Full article

In order to advance engineering applications of robotics such as wearable health-monitoring devices, humanoid robots, etc., it is essential to investigate the tactile sensations of artificial haptic sensors mimicking bioinspired human cutaneous mechanoreceptors such as free nerve endings, Merkel’s cells, Krause end bulbs, Meissner corpuscles, Ruffini endings, and Pacinian corpuscles. The generated receptor’s potential response to extraneous stimuli, categorized as slow adaption (SA) or fast adaption (FA), is particularly significant as a typical property. The present study addressed the estimation of SA and FA by utilizing morphologically fabricated mechanoreceptors made of our proposed magnetically responsive intelligent fluid, hybrid fluid (HF), and by applying our proposed electrolytic polymerization. Electric circuit models of the mechanoreceptors were generated using experimental data on capacitance and inductance on the basis of the electric characteristics of impedance. The present results regarding equivalent firing rates based on FA and SA are consistent with the FA and SA findings of vital mechanoreceptors by biomedical analysis. The present investigative process is useful to clarify the time of response to a force on the fabricated artificial mechanoreceptor. Full article

The plant protection unmanned aerial vehicle (UAV) scheduling model is of great significance to improve the operation income of UAV plant protection teams and ensure the quality of the operation. The simulated annealing algorithm (SA) is often used in the optimization solution of scheduling models, but the SA algorithm has the disadvantages of easily falling into local optimum and slow convergence speed. In addition, the current research on the UAV scheduling model for plant protection is mainly oriented to static scenarios. In the actual operation process, the UAV plant protection team often faces unexpected situations, such as new orders and changes in transfer path costs. The static model cannot adapt to such emergencies. In order to solve the above problems, this paper proposes to use the Levi distribution method to improve the simulated annealing algorithm, and it proposes a dynamic scheduling model driven by unexpected events, such as new orders and transfer path changes. Order sorting takes into account such factors as the UAV plant protection team’s operating income, order time window, and job urgency, and prioritizes job orders. In the aspect of order allocation and solution, this paper proposes a Levy annealing algorithm (Levy-SA) to solve the scheduling strategy of plant protection UAVs in order to solve the problem that the traditional SA is easy to fall into local optimum and the convergence speed is slow. This paper takes the plant protection operation scenario of “one spray and three defenses” for wheat in Nanjing City, Jiangsu Province, as an example, to test the plant protection UAV scheduling model under the dynamic conditions of new orders and changes in transfer costs. The results show that the plant protection UAV dynamic scheduling model proposed in this paper can meet the needs of plant protection UAV scheduling operations in static and dynamic scenarios. Compared with SA and greedy best first search algorithm (GBFS), the proposed Levy-SA has better performance in static and dynamic programming scenarios. It has more advantages in terms of man-machine adjustment distance and total operation time. This research can provide a scientific basis for the dynamic scheduling and decision analysis of plant protection UAVs, and provide a reference for the development of an agricultural machinery intelligent scheduling system. Full article

Soft actuators (SAs) have been used in many compliant robotic structure and wearable devices, due to their safe interaction with the wearers. Despite advances, the capability of current SAs is limited by scalability, high hysteresis, and slow responses. In this paper, a new class of soft, scalable, and high-aspect ratio fiber-reinforced hydraulic SAs is introduced. The new SA uses a simple fabrication process of insertion where a hollow elastic rubber tube is directly inserted into a constrained hollow coil, eliminating the need for the manual wrapping of an inextensible fiber around a long elastic structure. To provide high adaptation to the user skin for wearable applications, the new SAs are integrated into flexible fabrics to form a wearable fabric sleeve. To monitor the SA elongation, a soft liquid metal-based fabric piezoresistive sensor is also developed. To capture the nonlinear hysteresis of the SA, a novel asymmetric hysteresis model which only requires five model parameters in its structure is developed and experimentally validated. The new SAs-driven wearable robotic sleeve is scalable, highly flexible, and lightweight. It can also produce a large amount of force of around 23 N per muscle at around 30% elongation, to provide useful assistance to the human upper limbs. Experimental results show that the soft fabric sleeve can augment a user’s performance when working against a load, evidenced by a significant reduction on the muscular effort, as monitored by electromyogram (EMG) signals. The performance of the developed SAs, soft fabric sleeve, soft liquid metal fabric sensor, and nonlinear hysteresis model reveal that they can effectively modulate the level of assistance for the wearer. The new technologies obtained from this work can be potentially implemented in emerging assistive applications, such as rehabilitation, defense, and industry. Full article

The runtime behavior of Simulated Annealing (SA), similar to other metaheuristics, is controlled by hyperparameters. For SA, hyperparameters affect how “temperature” varies over time, and “temperature” in turn affects SA’s decisions on whether or not to transition to neighboring states. It is typically necessary to tune the hyperparameters ahead of time. However, there are adaptive annealing schedules that use search feedback to evolve the “temperature” during the search. A classic and generally effective adaptive annealing schedule is the Modified Lam. Although effective, the Modified Lam can be sensitive to the scale of the cost function, and is sometimes slow to converge to its target behavior. In this paper, we present a novel variation of the Modified Lam that we call Self-Tuning Lam, which uses early search feedback to auto-adjust its self-adaptive behavior. Using a variety of discrete and continuous optimization problems, we demonstrate the ability of the Self-Tuning Lam to nearly instantaneously converge to its target behavior independent of the scale of the cost function, as well as its run length. Our implementation is integrated into Chips-n-Salsa, an open-source Java library for parallel and self-adaptive local search. Full article