One of the current trends in robotics is to employ large language models (LLMs) to provide non-predefined command execution and natural human-robot interaction. It is useful to have an environment map together with it...
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While much work has been done recently in the realm of model-based control of soft robots and soft-rigid hybrids, most works examine robots that have an inherently serial structure. While these systems have been preva...
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ISBN:
(数字)9798350384574
ISBN:
(纸本)9798350384581
While much work has been done recently in the realm of model-based control of soft robots and soft-rigid hybrids, most works examine robots that have an inherently serial structure. While these systems have been prevalent in the literature, there is an increasing trend toward designing soft-rigid hybrids with intrinsically coupled elasticity between various degrees of freedom. In this work, we seek to address the issues of modeling and controlling such structures, particularly when underactuated. We introduce several simple models for elastic coupling, typical of those seen in these systems. We then propose a controller that compensates for the elasticity, and we prove its stability with Lyapunov methods without relying on the elastic dominance assumption. This controller is applicable to the general class of underactuated soft robots. After evaluating the controller in simulated cases, we then develop a simple hardware platform to evaluate both the models and the controller. Finally, using the hardware, we demonstrate a novel use case for underactuated, elastically coupled systems in "sensorless" force control.
The article describes an optical method for obtaining the geometric parameters of an object, based on the analysis of the boundaries of the object's shadow in a divergent light flux. One of the main tasks that ari...
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Aiming at the problems that the existing networks do not adapt to the image characteristics of edge scenes, do not effectively process the detail information in images and have insufficient feature fusion, this thesis...
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Deep Reinforcement Learning techniques are achieving state-of-the-art results in robust legged locomotion. While there exists a wide variety of legged platforms such as quadruped, humanoids, and hexapods, the field is...
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The lightweight Unmanned Aerial Vehicle (UAV) flight activities are constrained, particularly in the UAV range or activity span and perseverance, by the strategic correspondence link capabilities. This paper tends to ...
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With the rapid development of deep learning, the increasing complexity and scale of parameters make training a new model increasingly resource-intensive. In this paper, we start from the classic convolutional neural n...
The field of Human-Robot Interaction (HRI) is swiftly expanding, driven by notable advancements in artificial intelligence (AI). Humanoid robots, now capable of being equipped with advanced AI models, are being consid...
The field of Human-Robot Interaction (HRI) is swiftly expanding, driven by notable advancements in artificial intelligence (AI). Humanoid robots, now capable of being equipped with advanced AI models, are being considered for a wide array of applications due to their ability to perform complex tasks and interact with humans in both natural and intelligent ways. In the domain of social robotics, the capability to selectively interact with authorized users is crucial for ensuring security and providing personalized user experiences. Unimodal user recognition methods, such as audio-based user recognition, are commonly used in social robots. However, these methods can be susceptible to ambient noise and might exhibit reduced accuracy. Although face recognition modality is often employed to enhance accuracy, the majority of audio-visual person recognition methods are trained on datasets with only a single user in the *** paper introduces a method for audio-visual user recognition with multiple users in the frame, utilizing an additional sound localization modality. The proposed method is evaluated using a dataset created from interactions between the social robot Pepper and multiple users. The results demonstrated that the proposed method significantly outperformed unimodal user recognition methods.
Soft robot perception integrates information from distributed, multi-modal sensors, broadening their application to active interaction. Our work introduces recurrent learning models for tactile-based object recognitio...
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Learning from Demonstration (LfD) stands out as a powerful tool for swiftly deploying tasks in robotics, distinguished by its capacity to effectively leverage the task expertise of experts. However, contemporary robot...
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