In recent years, the perceptual capabilities of robots have been significantly enhanced. However, the task execution of the robots still lacks adaptive capabilities in unstructured and dynamic ...environments.
In this paper, we propose an ontology based autonomous robot task processing framework (ARTProF), to improve the robot's adaptability within unstructured and dynamic environments. ARTProF unifies ontological knowledge representation, reasoning, and autonomous task planning and execution into a single framework. The interface between the knowledge base and neural network-based object detection is first introduced in ARTProF to improve the robot's perception capabilities. A knowledge-driven manipulation operator based on Robot Operating System (ROS) is then designed to facilitate the interaction between the knowledge base and the robot's primitive actions. Additionally, an operation similarity model is proposed to endow the robot with the ability to generalize to novel objects. Finally, a dynamic task planning algorithm, leveraging ontological knowledge, equips the robot with adaptability to execute tasks in unstructured and dynamic environments.
Experimental results on real-world scenarios and simulations demonstrate the effectiveness and efficiency of the proposed ARTProF framework.
In future work, we will focus on refining the ARTProF framework by integrating neurosymbolic inference.
Graphitic carbon nitride (g-C₃N₄) nanosheets were exfoliated from bulk g-C₃N₄ and utilized to improve the sensing performance of a pure graphene sensor for the first time. The role of hydrochloric ...acid treatment on the exfoliation result was carefully examined. The exfoliated products were characterized by X-ray diffraction (XRD) patterns, scanning electron microscopy (SEM), atomic force microscopy (AFM), and UV-Vis spectroscopy. The exfoliated g-C₃N₄ nanosheets exhibited a uniform thickness of about 3-5 nm and a lateral size of about 1-2 µm. A g-C₃N₄/graphene nanocomposite was prepared via a self-assembly process and was demonstrated to be a promising sensing material for detecting nitrogen dioxide gas at room temperature. The nanocomposite sensor exhibited better recovery as well as two-times the response compared to pure graphene sensor. The detailed sensing mechanism was then proposed.
Consistency analysis is a crucial topic for preference relations. This paper studies the consistency of interval linguistic fuzzy preference relations (ILFPRs) using the constrained interval ...linguistic arithmetic and introduces a new consistency definition. Then, several properties of this definition are researched. Meanwhile, the connection between this concept and a previous one is discussed. Following this concept, programming models for judging the consistency and for deriving consistent ILFPRs are constructed, respectively. Considering the case that incomplete ILFPRs may be obtained, a programming model for obtaining missing judgments following the consistency discussion is built. Afterwards, the consensus for group decision making (GDM) is studied and a model for adjusting individual ILFPRs to reach the consensus threshold is established. Consequently, an interactive procedure for GDM with ILFPRs is presented. A practical problem is provided to illustrate the utilization of the new algorithm and comparative discussion is offered.
Various laser scanning strategies of multitrack products, consisting of a default Raster pattern (R1), a Raster pattern with a changed line order (R2), and a default Zigzag pattern (Z1), with ...different overlap rates ranged from 0.7 to 0.5, have been conducted to investigate microstructure evolution for Mg–3Al–1Zn alloy. As the overlap rate changes from 0.7 to 0.5, the average grain size decreases and the texture is slightly concentrated, except for R2 pattern. For effect of different scanning pattern, a relatively small average grain size can be obtained using the R1, R2 patterns compared to using the Z1 pattern; a relatively weak texture can be obtained using the R1, Z1 patterns compared to using the R2 pattern. The utilization of Z1 pattern results in a further texture weakening compared to that of the R1 pattern. Microstructure evolution of scanning strategy is mainly determined by low-undercooling-required epitaxial growth along temperature gradient directions at the solid/liquid interface. Combined with computational thermal-fluid dynamics simulation, a strong fluid flow within the molten pool promotes side expansion of the molten pool, resulting in the larger overlap area, the corresponding three-times remelting domain and continuous deflections of grain major axes.
The presence of strong ambient vibrations could have a negative impact on applications such as high precision inertial navigation and tilt measurement due to the vibration rectification error (VRE) ...of the accelerometer. In this paper, we investigate the origins of the VRE using a self-developed MEMS accelerometer equipped with an area-variation-based capacitive displacement transducer. Our findings indicate that the second-order nonlinearity coefficient is dependent on the frequency but the VRE remains constant when the displacement amplitude of the excitation is maintained at a constant level. This frequency dependence of nonlinearity is a result of several factors coupling with each other during signal conversion from acceleration to electrical output signal. These factors include the amplification of the proof mass's amplitude as the excitation frequency approaches resonance, the nonlinearity in capacitance-displacement conversion at larger displacements caused by the fringing effect, and the offset of the mechanical suspension's equilibrium point from the null position of the differential capacitance electrodes. Through displacement transducer and damping optimization, the second-order nonlinearity coefficient is greatly reduced from mg/g2 to μg/g2.
Most of the current crop row detection algorithms focus on extracting crop canopy rows as location information. However, for some high-pole crops, due to the transverse deviation of the position of ...the canopy and roots, the agricultural machinery can easily cause the wheel to crush the crop when it is automatically driven. In fact, it is more accurate to use the crop root row as the feature for its location calibration, so a method of crop root row detection is proposed in this paper. Firstly, the ROI (region of interest) of the crop canopy is extracted by a semantic segmentation algorithm, then crop canopy row detection lines are extracted by the horizontal strip division and the midpoint clustering method within the ROI. Next, the Crop Root Representation Learning Model learns the Representation of the crop canopy row and crop root row to obtain the Alignment Equation. Finally, the crop canopy row detection lines are modified according to the Alignment Equation parameters to obtain crop root row detection lines. The average processing time of a single frame image (960 × 540 pix) is 30.49 ms, and the accuracy is 97.1%. The research has important guiding significance for the intelligent navigation, tilling, and fertilization operation of agricultural machinery.
This paper presents a micromachined micro-g capacitive accelerometer with a silicon-based spring-mass sensing element. The displacement changes of the proof mass are sensed by an area-variation-based ...capacitive displacement transducer that is formed by the matching electrodes on both the movable proof mass die and the glass cover plate through the flip-chip packaging. In order to implement a high-performance accelerometer, several technologies are applied: the through-silicon-wafer-etching process is used to increase the weight of proof mass for lower thermal noise, connection beams are used to reduce the cross-sensitivity, and the periodic array area-variation capacitive displacement transducer is applied to increase the displacement-to-capacitance gain. The accelerometer prototype is fabricated and characterized, demonstrating a scale factor of 510 mV/g, a noise floor of 2 µg/Hz
at 100 Hz, and a bias instability of 4 µg at an averaging time of 1 s. Experimental results suggest that the proposed MEMS capacitive accelerometer is promising to be used for inertial navigation, structural health monitoring, and tilt measurement applications.
As the basic link of autonomous navigation in agriculture, crop row detection is vital to achieve accurate detection of crop rows for autonomous navigation. Machine vision algorithms are easily ...affected by factors such as changes in field lighting and weather conditions, and the majority of machine vision algorithms detect early periods of crops, but it is challenging to detect crop rows under high sheltering pressure in the middle and late periods. In this paper, a crop row detection algorithm based on LiDAR is proposed that is aimed at the middle and late crop periods, which has a good effect compared with the conventional machine vision algorithm. The algorithm proposed the following three steps: point cloud preprocessing, feature point extraction, and crop row centerline detection. Firstly, dividing the horizontal strips equally, the improved K-means algorithm and the prior information of the previous horizontal strip are utilized to obtain the candidate points of the current horizontal strip, then the candidate points information is used to filter and extract the feature points in accordance with the corresponding threshold, and finally, the least squares method is used to fit the crop row centerlines. The experimental results show that the algorithm can detect the centerlines of crop rows in the middle and late periods of maize under the high sheltering environment. In the middle period, the average correct extraction rate of maize row centerlines was 95.1%, and the average processing time was 0.181 s; in the late period, the average correct extraction rate of maize row centerlines was 87.3%, and the average processing time was 0.195 s. At the same time, it also demonstrates accuracy and superiority of the algorithm over the machine vision algorithm, which can provide a solid foundation for autonomous navigation in agriculture.
A large area of randomly distributed nanospike as nanostructured template was induced by femtosecond (fs) laser on a silicon substrate in water. Copper oxide (CuO) and palladium (Pd) heterostructured ...nanofilm were coated on the nanospikes by magnetron sputtering technology and vacuum thermal evaporation coating technology respectively for the construction of a p-type hydrogen sensor. Compared with the conventional gas sensor based on CuO working at high temperature, nanostructured CuO/Pd heterostructure exhibited promising detection capability to hydrogen at room temperature. The detection sensitivity to 1% H
was 10.8%, the response time was 198 s, and the detection limit was as low as 40 ppm, presenting an important application prospect in the clean energy field. The excellent reusability and selectivity of the CuO/Pd heterostructure sensor toward H
at room temperature were also demonstrated by a series of cyclic response characteristics. It is believed that our room-temperature hydrogen sensor fabricated with a waste-free green process, directly on silicon substrate, would greatly promote the future fabrication of a circuit-chip integrating hydrogen sensor.
An efficient copper‐catalyzed trifluoromethylation of trisubstituted allylic and homoallylic alcohols with Togni’s reagent has been developed. This strategy, accompanied by a double‐bond migration, ...leads to various branched CF3‐substituted alcohols by using readily available trisubstituted cyclic/acyclic alcohols as substrates. Moreover, for alcohols in which β‐H elimination is prohibited, CF3‐containing oxetanes are isolated as the sole product.
An efficient copper‐catalyzed trifluoromethylation of trisubstituted allylic and homoallylic alcohols with Togni's reagent has been developed. This strategy, accompanied by a double‐bond migration, leads to various branched CF3‐substituted alcohols by using readily available trisubstituted cyclic/acyclic alcohols as substrates. Moreover, for alcohols in which β‐H elimination is prohibited, CF3‐containing oxetanes are isolated as the sole product.
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