The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection *** materials are promising candidates for next-generation photodetectors(PDs)due to thei...
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The rapid advancement of nanotechnology has sparked much interest in applying nanoscale perovskite materials for photodetection *** materials are promising candidates for next-generation photodetectors(PDs)due to their unique optoelectronic properties and flexible synthesis *** review explores the approaches used in the development and use of optoelectronic devices made of different nanoscale perovskite architectures,including quantum dots,nanosheets,nanorods,nanowires,and *** a thorough analysis of recent literature,the review also addresses common issues like the mechanisms underlying the degradation of perovskite PDs and offers perspectives on potential solutions to improve stability and scalability that impede widespread *** addition,it highlights that photodetection encompasses the detection of light fields in dimensions other than light intensity and suggests potential avenues for future research to overcome these obstacles and fully realize the potential of nanoscale perovskite materials in state-of-the-art photodetection *** review provides a comprehensive overview of nanoscale perovskite PDs and guides future research efforts towards improved performance and wider applicability,making it a valuable resource for researchers.
With the advancement of intelligent manufacturing, an increasing number of industrial production processes are transforming unmanned operations. This trend is particularly evident in factories that involve potential s...
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ISBN:
(数字)9798350394085
ISBN:
(纸本)9798350394092
With the advancement of intelligent manufacturing, an increasing number of industrial production processes are transforming unmanned operations. This trend is particularly evident in factories that involve potential safety hazards, where the demand for unmanned production is becoming increasingly urgent. Teleoperation, as a core technology for achieving unmanned factories, holds tremendous importance in keeping workers safe from danger. However, traditional teleoperation strategies encounter challenges due to mismatches between master and slave workspaces, making it difficult to achieve both high precision and operation across large workspaces simultaneously. To address this issue, this paper proposes an event-triggered control strategy for a teleoperated robot system. By introducing a foot pedal as the event-triggered switch, the enablement and termination of teleoperation are associated with the activation of the pedal. Through resetting the start position, fine-grained teleoperation is achieved throughout the entire workspace of the robot. To demonstrate the advantages of the proposed control strategy, a mimicked wiring operation task scenario is constructed for experimental verification, and the teleoperation tasks are completed successfully and efficiently.
In this paper it is presented a Hardware-in-the-loop (HIL) mobile robot programming approach, to be applied in a robotics educational context. The motivation to apply this approach is the fact that students can progra...
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ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981
In this paper it is presented a Hardware-in-the-loop (HIL) mobile robot programming approach, to be applied in a robotics educational context. The motivation to apply this approach is the fact that students can program the robots without access to the robot hardware, but still maintain some important closed loop control critical features, such as a realistic lag time and the possibility for a larger number of students to program at the same time. Therefore, the developed software is applied to the real hardware without any change. The HIL approach was applied to provide a simulation close to reality, once the processing occurs in the real robot processor and the actuation and sensorization inside the simulation, adding to the advantage to test the firmware avoiding damage in the physical robot.
Several data compressors have been proposed in distributed optimization frameworks of network systems to reduce communication overhead in large-scale applications. In this paper, we demonstrate that effective informat...
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This article presents the prototyping of an educational manipulator robot, based on the "EEZYbotARM Mk2" robot, tailored for first-year master’s students in the field of robotics. The project encompasses th...
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ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981
This article presents the prototyping of an educational manipulator robot, based on the "EEZYbotARM Mk2" robot, tailored for first-year master’s students in the field of robotics. The project encompasses the assembly of the robot arm, computation of both forward and inverse kinematics, and analysis of two path-planning movement algorithms. These features are consolidated into an Arduino library to streamline the process for students to generate instructions for the robot. The "EEZYbotARM Mk2" features a three-degree-of-freedom revolute arm with a gripper that remains parallel to its base at all times, enhancing its suitability for educational applications such as pick-and-place tasks. The article provides detailed descriptions of the materials and methods employed, along with proposed challenges for student engagement.
Photocatalytic water splitting using semiconductor catalysts for green hydrogen production is a critical step toward global carbon neutrality. However, the rapid decline in catalytic activity due to unstable molecular...
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In this article, a rehabilitation exoskeleton assisted by lateral walking is designed to help patients with lower limb movement disorders to solve the problem of lateral walking assistance, so as to achieve the effect...
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Accurate rigid-body dynamics is crucial for serial industrial robot applications such as force control and physical human-robot interaction. Despite decades of research, the precise identification of dynamic parameter...
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Due to saturated regions of inputting low dynamic range (LDR) images and large intensity changes among the LDR images caused by different exposures, it is challenging to produce an information enriched panoramic LDR i...
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To develop robots that can show cognitive functions, we must learn from the knowledge of human cognition. Existing biological and psychological evidence suggests that self-face perception and sensorimotor learning mec...
To develop robots that can show cognitive functions, we must learn from the knowledge of human cognition. Existing biological and psychological evidence suggests that self-face perception and sensorimotor learning mechanisms play a crucial role in self-recognition. However, one of the most important self-identity cues – facial information – has not been extensively studied in the robot self-recognition task. Current research on robot self-recognition primarily relies on the recognition of high-precision targets and tracking of manipulator motions, where the self-perception of facial information is not well studied. In this work, we propose a novel approach to achieve self-recognition via self-perception of facial expressions. Specifically, we developed a Conditional Generative Adversarial Network (CGAN) model using the knowledge on human cognitive and sensorimotor functions. It allows the robot to be aware of self-face (i.e., off-line model). Passing the observed visual variations in a mirror and comparing them to self-perceptive information, the robot can recognize the self through an online Bayesian learning regression. The results of our first experiment show that the robot can recognize itself in a mirror. The results from the second experiment show that our algorithm could be tricked by a similar robot with the same facial expressions, which is similar to the rubber hand illusion (RHI).
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