The robustness of visual navigation policies trained through imitation often hinges on the augmentation of the training image-action pairs. Traditionally, this has been done by collecting data from multiple cameras, b...
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ISBN:
(纸本)9781728196817
The robustness of visual navigation policies trained through imitation often hinges on the augmentation of the training image-action pairs. Traditionally, this has been done by collecting data from multiple cameras, by using standard data augmentations from computer vision, such as adding random noise to each image, or by synthesizing training images. In this paper we show that there is another practical alternative for data augmentation for visual navigation based on extrapolating viewpoint embeddings and actions nearby the ones observed in the training data. Our method makes use of the geometry of the visual navigation problem in 2D and 3D and relies on policies that are functions of equivariant embeddings, as opposed to images. Given an image-action pair from a training navigation dataset, our neural network model predicts the latent representations of images at nearby viewpoints, using the equivariance property, and augments the dataset. We then train a policy on the augmented dataset. Our simulation results indicate that policies trained in this way exhibit reduced cross-track error, and require fewer interventions compared to policies trained using standard augmentation methods. We also show similar results in autonomous visual navigation by a real ground robot along a path of over 500m.
Visual navigation for insect-scale robots is very challenging because in such a small scale, the size, weight, and power (SWaP) constraints do not appear to permit visual navigation techniques such as SLAM (Simultaneo...
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ISBN:
(数字)9781665479271
ISBN:
(纸本)9781665479271
Visual navigation for insect-scale robots is very challenging because in such a small scale, the size, weight, and power (SWaP) constraints do not appear to permit visual navigation techniques such as SLAM (Simultaneous Localization and Mapping) because they are likely to be too power-hungry. We propose to use a biology-inspired approach, which we term the bilinear optic flow approximation, that is more computationally efficient. We build on previous work that has shown that the bilinear approximation can be used for visual servoing. Here, we show that a bilinear approximator can be learned that is able to stabilize the heading of a robot while performing continuous forward motion in a corridor-shaped environment. This is a necessary capability for confined-space navigation that insect-sized robots are likely to perform. In this work, we describe the underlining methodology of the method and built a 2D visual simulation environment and omnidirectional camera model to validate our results.
Graphic technology rapidly evolve nowadays. The content creation becomes a very important direction and number of people involved in it grows every year. There are three main industries which employs specialists in co...
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Under shared autonomy, wheelchair users expect vehicles to provide safe and comfortable rides while following users' high-level navigation plans. To find such a path, vehicles negotiate with different terrains and...
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ISBN:
(数字)9781665479271
ISBN:
(纸本)9781665479271
Under shared autonomy, wheelchair users expect vehicles to provide safe and comfortable rides while following users' high-level navigation plans. To find such a path, vehicles negotiate with different terrains and assess their traversal difficulty. Most prior works model surroundings either through geometric representations or semantic classifications, which do not reflect perceived motion intensity and ride comfort in downstream navigation tasks. We propose to model ride comfort explicitly in traversability analysis using proprioceptive sensing. We develop a self-supervised learning framework to predict traversability costmap from first-person-view images by leveraging vehicle states as training signals. Our approach estimates how the vehicle would "feel" if traversing over based on terrain appearances. We then show our navigation system provides human-preferred ride comfort through robot experiments together with a human evaluation study. The project could be found at https://***/ view/rca-navigation.
Combining 5G technology with artificial intelligence technology is an important way to develop and improve 5G technology, but the current 5G technology is still in the exploratory stage and needs improvement. It shoul...
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In surgery, accurate localization of critical structures like blood vessels is crucial, yet current 2D visualization methods limit precision and increase cognitive load for surgeons. This paper introduces a markerless...
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ISBN:
(数字)9798331514846
ISBN:
(纸本)9798331525637
In surgery, accurate localization of critical structures like blood vessels is crucial, yet current 2D visualization methods limit precision and increase cognitive load for surgeons. This paper introduces a markerless registration approach that uses only sensors in a Head-Mounted Display to align CT/MRI data directly onto the patient in a 3D space. Point clouds extracted from CT/MRI data are registered with world captures from the Head-Mounted Display’s time-of-flight camera, allowing for precise visualization. We evaluated the system using physical measurements on phantoms and compared algorithmic registration to manual alignment. The results show a registration error of approx. 4.87±0.05mm, demonstrating the potential of this technique for preoperative planning and intraoperative support.
The purpose of this paper is to construct ontology based on ‘Compendium of Materia Medica’ and to explore the knowledge organization, representation and mining methods of ancient Chinese medicine books. The classifi...
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ISBN:
(数字)9798331504946
ISBN:
(纸本)9798331504953
The purpose of this paper is to construct ontology based on ‘Compendium of Materia Medica’ and to explore the knowledge organization, representation and mining methods of ancient Chinese medicine books. The classification system of ‘Compendium of Materia Medica’ was introduced, including the three-level structure and classification basis of department, class and species, which provided the basis of class and attribute definition for ontology construction. The concept category extraction method is described, and the categories such as origin and release are extracted according to the drug description structure. The ontology construction adopts the Stanford seven-step method, and the ontology visualization is displayed. The research results can be applied to clinical diagnosis and treatment to assist doctors in obtaining drug information.
Deep Metric Learning (DML) proposes to learn metric spaces which encode semantic similarities as embedding space distances. These spaces should be transferable to classes beyond those seen during training. Commonly, D...
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ISBN:
(数字)9781665469463
ISBN:
(纸本)9781665469463
Deep Metric Learning (DML) proposes to learn metric spaces which encode semantic similarities as embedding space distances. These spaces should be transferable to classes beyond those seen during training. Commonly, DML methods task networks to solve contrastive ranking tasks defined over binary class assignments. However, such approaches ignore higher-level semantic relations between the actual classes. This causes learned embedding spaces to encode incomplete semantic context and misrepresent the semantic relation between classes, impacting the generalizability of the learned metric space. To tackle this issue, we propose a language guidance objective for visual similarity learning. Leveraging language embeddings of expert- and pseudo-classnames, we contextualize and realign visual representation spaces corresponding to meaningful language semantics for better semantic consistency. Extensive experiments and ablations provide a strong motivation for our proposed approach and show language guidance offering significant, model-agnostic improvements for DML, achieving competitive and state-ofthe-art results on all benchmarks.
In the realm of industrial automation, smooth communication between Programmable Logic Controllers (PLCs) and monitoring systems is paramount. This article extensively explores into the application of Modbus/TCP commu...
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ISBN:
(数字)9798350361643
ISBN:
(纸本)9798350361650
In the realm of industrial automation, smooth communication between Programmable Logic Controllers (PLCs) and monitoring systems is paramount. This article extensively explores into the application of Modbus/TCP communication technology in PLCs integration. Initially, a brief overview of the Modbus/TCP protocol and its significance in industrial settings is provided. Subsequently, intricate system architectures are thoroughly explored, focusing on the setup involving PLCs and Modbus/TCP servers. To effectively visualize and interpret data, a dedicated web platform for retrieving data from industrial systems via Modbus/TCP communication has been devised.
Employing a learning medium can support learning and teaching activities. This learning medium can be one way to help students in understanding particular lessons, e.g., mathematics, art, and science. Although due to ...
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