检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Wang, Yuning Zhang, Pu Bai, Lei Xue, Jianru Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University China DiDi Chuxing China Shanghai AI Laboratory China

Scene information plays a crucial role in trajectory forecasting systems for autonomous driving by providing semantic clues and constraints on potential future paths of traffic agents. Prevalent trajectory prediction techniques often take high-definition maps (HD maps) as part of the inputs to provide scene knowledge. Although HD maps offer accurate road information, they may suffer from the high cost of annotation or restrictions of law that limits their widespread use. Therefore, those methods are still expected to generate reliable prediction results in mapless scenarios. In this paper, we tackle the problem of improving the consistency of multi-modal prediction trajectories and the real road topology when map information is unavailable during the test phase. Specifically, we achieve this by training a map-based prediction teacher network on the annotated samples and transferring the knowledge to a student mapless prediction network using a two-fold knowledge distillation framework. Our solution is generalizable for common trajectory prediction networks and does not bring extra computation burden. Experimental results show that our method stably improves prediction performance in mapless mode on many widely used state-of-the-art trajectory prediction baselines, compensating for the gaps caused by the absence of HD maps. Qualitative visualization results demonstrate that our approach helps infer unseen map information. © 2023, CC BY-NC-SA.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Function-oriented optimization design method for underactuated tendon-driven humanoid prosthetic hand

引用

Frontiers of Mechanical Engineering 2022年第3期17卷 75-89页

作者： Yue ZHENG Xiangxin LI Lan TIAN Guanglin LI CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology(SIAT)Chinese Academy of Sciences(CAS)Shenzhen518055China Shenzhen College of Advanced Technology University of Chinese Academy of SciencesShenzhen518055China SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for SocietyShenzhen518055China Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen518055China

The loss of hand functions in upper limb amputees severely restricts their mobility in daily *** a humanoid prosthetic hand would be an effective way of restoring lost hand *** a prosthetic hand design,replicating the natural and dexterous grasping functions with a few actuators remains a big *** this study,a function-oriented optimization design(FOD)method is proposed for the design of a tendon-driven humanoid prosthetic *** optimization function of different functional conditions of full-phalanx contact,total contact force,and force isotropy was constructed based on the kinetostatic model of a prosthetic finger for the evaluation of grasping *** a genetic algorithm,the optimal geometric parameters of the prosthetic finger could be determined for specific functional *** results reveal that the structure of the prosthetic finger is significantly different when designed for different functional requirements and grasping target sizes.A prosthetic finger was fabricated and tested with grasping *** mean absolute percentage error between the theoretical value and the experimental result is less than 10%,demonstrating that the kinetostatic model of the prosthetic finger is effective and makes the FOD method *** study suggests that the FOD method enables the systematic evaluation of grasping performance for prosthetic hands in the design stage,which could improve the design efficiency and help prosthetic hands meet the design requirements.

关键词： function-oriented tendon driven prosthetic hand optimization humanoid underactuated

来源：评论

学校读者我要写书评

暂无评论

AI-Enhanced Decision Support for Optimized Carbon Quota Allocation Across Industrial Sectors

AI-Enhanced Decision Support for Optimized Carbon Quota Allo...

引用

IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Baichuan Liu Wenxuan Liu Junhua Zhao School of Science and Engineering The Chinese University of Hong Kong Shenzhen Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) Shenzhen China

ISBN: (数字)9798331523527

ISBN: (纸本)9798331523534

To mitigate greenhouse gas emissions, governments allocate carbon quotas to industries under Emission Trading Systems. Allocating these quotas involves complex modeling challenges that require effective distribution strategies, which traditional Multi-Criteria Decision Analysis (MCDA) methods struggle to address comprehensively. These methods often fall short of encapsulating the preferences of policymakers and the distinct characteristics of different industries. In response, this paper proposes a novel framework termed the Large Language Model Carbon Quota Allocation Assistant (QAA). The QAA framework combines classical decision-making approaches with a robust expert knowledge base, enhancing the adaptability of allocation schemes to meet specific user demands and industry-specific characteristics. We validate this model through an empirical study involving the allocation of carbon quotas among six major emitting industries in Guangdong, China. The results are analyzed and compared against those derived from conventional linear combination weighting methods. Our findings substantiate the superior efficacy of the QAA, demonstrating its capability to optimize the monetary value of carbon quotas by harmoniously integrating user requirements and expert insights. This study not only underscores the potential of large language models in environmental policymaking but also sets a precedent for future research in this domain.

关键词： Industries Adaptation models Analytical models Large language models Carbon dioxide System integration Real-time systems MCDM Resource management Carbon

来源：评论

学校读者我要写书评

暂无评论

Discrepant and Multi-instance Proxies for Unsupervised Person Re-identification

Discrepant and Multi-instance Proxies for Unsupervised Perso...

引用

International Conference on Computer Vision (ICCV)

作者： Chang Zou Zeqi Chen Zhichao Cui Yuehu Liu Chi Zhang School of Software Engineering Xi’an Jiaotong University Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Chang’an University

Most recent unsupervised person re-identification methods maintain a cluster uni-proxy for contrastive learning. However, due to the intra-class variance and inter-class similarity, the cluster uni-proxy is prone to be biased and confused with similar classes, resulting in the learned features lacking intra-class compactness and inter-class separation in the embedding space. To completely and accurately represent the information contained in a cluster and learn discriminative features, we propose to maintain discrepant cluster proxies and multi-instance proxies for a cluster. Each cluster proxy focuses on representing a part of the information, and several discrepant proxies collaborate to represent the entire cluster completely. As a complement to the overall representation, multi-instance proxies are used to accurately represent the fine-grained information contained in the instances of the cluster. Based on the proposed discrepant cluster proxies, we construct cluster contrastive loss to use the proxies as hard positive samples to pull instances of a cluster closer and reduce intraclass variance. Meanwhile, instance contrastive loss is constructed by global hard negative sample mining in multiinstance proxies to push away the truly indistinguishable classes and decrease inter-class similarity. Extensive experiments on Market-1501 and MSMT17 demonstrate that the proposed method outperforms state-of-the-art approaches.

关键词：

来源：评论

学校读者我要写书评

暂无评论

NUSense: Robust Soft Optical Tactile Sensor

arXiv

引用

arXiv 2024年

作者： Yergibay, Madina Mussin, Tleukhan Seitzhan, Saltanat Kenzhebek, Daryn Kappassov, Zhanat Soh, Harold Taunyazov, Tasbolat Robotics Department Institute of Smart Systems and Artificial Intelligence Nazarbayev University Astana Kazakhstan Dept. of Computer Science National University of Singapore Singapore

While most tactile sensors rely on measuring pressure, insights from continuum mechanics suggest that measuring shear strain provides critical information for tactile sensing. In this work, we introduce an optical tactile sensing principle based on shear strain detection. A silicone rubber layer, dyed with color inks, is used to quantify the shear magnitude of the sensing layer. This principle was validated using the NUSense camera-based tactile sensor. The wide-angle camera captures the elongation of the soft pad under mechanical load, a phenomenon attributed to the Poisson effect. The physical and optical properties of the inked pad are essential and should ideally remain stable over time. We tested the robustness of the sensor by subjecting the outermost layer to multiple load cycles using a robot arm. Additionally, we discussed potential applications of this sensor in force sensing and contact localization. Copyright © 2024, The Authors. All rights reserved.

关键词： Silicones

来源：评论

学校读者我要写书评

暂无评论

CaMP: causal multi-policy planning for interactive navigation in multi-room scenes 23

CaMP: causal multi-policy planning for interactive navigatio...

引用

Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Xiaohan Wang Yuehu Liu Xinhang Song Beibei Wang Shuqiang Jiang Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Science

Visual navigation has been widely studied under the assumption that there may be several clear routes to reach the goal. However, in more practical scenarios such as a house with several messy rooms, there may not. Interactive Navigation (InterNav) considers agents navigating to their goals more effectively with object interactions, posing new challenges of learning interaction dynamics and extra action space. Previous works learn single vision-to-action policy with the guidance of designed representations. However, the causality between actions and outcomes is prone to be confounded when the attributes of obstacles are diverse and hard to measure. Learning policy for long-term action planning in complex scenes also leads to extensive inefficient exploration. In this paper, we introduce a causal diagram of InterNav clarifying the confounding bias caused by obstacles. To address the problem, we propose a multi-policy model that enables the exploration of counterfactual interactions as well as reduces unnecessary exploration. We develop a large-scale dataset containing 600k task episodes in 12k multi-room scenes based on the ProcTHOR simulator and showcase the effectiveness of our method with the evaluations on our dataset.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Study of AI-based Harbor Surveillance System

A Study of AI-based Harbor Surveillance System

引用

International Conference on Advanced Communication Technology (ICACT)

作者： Dongkoo Shon Jeongsik Kim Tae Hyun Yoon Woo-Sung Jung Dae Seung Yoo Intelligent Robotics Research Division Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute Daejeon Republic of Korea

When ships of various types and sizes enter and depart from ports, the risk of collision between ships is high. In particular, collisions between large ships can lead to major accidents. In order to avoid crashes, it is important to quickly identify hazardous situations in advance using harbor surveillance system. But, the harbor surveillance system has limitations in that it continuously requires manpower and the criteria for judgment are different for each person. To solve this problem, we propose an AI based harbor surveillance system including image-based object recognition and abnormal situation recognition. Its superiority was proven through simulation. In the object recognition, YOLOv5, which had the best performance with an mAP of 0.953, was used. The abnormal situation was determined through the distance between the recognized objects, and the comparison of the determination results for 21.5 seconds (66 samples) showed 100%.

关键词： Image recognition Surveillance Seaports Computer crashes Communications technology Object recognition Marine vehicles

来源：评论

学校读者我要写书评

暂无评论

Diffusion model with cross attention as an inductive bias for disentanglement 24

Diffusion model with cross attention as an inductive bias fo...

引用

Proceedings of the 38th International Conference on Neural Information Processing Systems

作者： Tao Yang Cuiling Lan Yan Lu Nanning Zheng National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications and Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China Microsoft Research Asia

ISBN: (纸本)9798331314385

Disentangled representation learning strives to extract the intrinsic factors within the observed data. Factoring these representations in an unsupervised manner is notably challenging and usually requires tailored loss functions or specific structural designs. In this paper, we introduce a new perspective and framework, demonstrating that diffusion models with cross-attention itself can serve as a powerful inductive bias to facilitate the learning of disentangled representations. We propose to encode an image into a set of concept tokens and treat them as the condition of the latent diffusion model for image reconstruction, where cross attention over the concept tokens is used to bridge the encoder and the U-Net of the diffusion model. We analyze that the diffusion process inherently possesses the time-varying information bottlenecks. Such information bottlenecks and cross attention act as strong inductive biases for promoting disentanglement. Without any regularization term in the loss function, this framework achieves superior disentanglement performance on the benchmark datasets, surpassing all previous methods with intricate designs. We have conducted comprehensive ablation studies and visualization analyses, shedding a light on the functioning of this model. We anticipate that our findings will inspire more investigation on exploring diffusion model for disentangled representation learning towards more sophisticated data analysis and understanding.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Vehicle Trajectory Prediction with Soft Behavior Constraints

Vehicle Trajectory Prediction with Soft Behavior Constraints

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Ke Ye Sanping Zhou Miao Kang Jingwen Fu Nanning Zheng National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and Applications and Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Shaanxi China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Trajectory prediction plays a crucial role in autonomous driving, but it is challenging due to the multi-modal nature of future trajectories. Behavior information is frequently employed to capture more diverse modalities of future trajectories. Traditional behavior information is typically hard-encoded, which is often inaccurate and inadequate for reflecting future multimodality. Therefore, we introduce the concept of soft vehicle behavior, which is represented as a probability distribution over a predefined comprehensive set of behaviors. This approach allows for a more rational depiction of vehicle behavior and captures potential future driving modalities. Based on it, we propose a new soft-behavior-constrained vehicle trajectory prediction framework. The framework consists of a backbone and a lightweight and plug-and-play behavior prediction module, which is used to imbue soft behavior constraints to assist in representation learning. We integrated the behavior prediction module into five representative trajectory predictors and achieved improvements of at least 4.2% in minFDE(K=5) on the nuScenes dataset and 0.5% in minFDE(K=6) on the Argoverse 1 motion forecasting dataset. These universal increments prove the effectiveness and generalizability of soft behavior constraints in vehicle trajectory prediction.

关键词： Representation learning Space vehicles Philosophical considerations Pedestrians Buildings Predictive models Probability distribution Trajectory Forecasting Intelligent robots

来源：评论

学校读者我要写书评

暂无评论

Efficient LiDAR Bundle Adjustment for Multi-Scan Alignment Utilizing Continuous-Time Trajectories

arXiv

引用

arXiv 2024年

作者： Wiesmann, Louis Marks, Elias Gupta, Saurabh Guadagnino, Tiziano Behley, Jens Stachniss, Cyrill The Center for Robotics University of Bonn Germany The Department of Engineering Science The University of Oxford United Kingdom The Lamarr Institute for Machine Learning and Artificial Intelligence Germany

Constructing precise global maps is a key task in robotics and is required for localization, surveying, monitoring, or constructing digital twins. To build accurate maps, data from mobile 3D LiDAR sensors is often used. Mapping requires correctly aligning the individual point clouds to each other to obtain a globally consistent map. In this paper, we investigate the problem of multi-scan alignment to obtain globally consistent point cloud maps. We propose a 3D LiDAR bundle adjustment approach to solve the global alignment problem and jointly optimize the available data. Utilizing a continuous-time trajectory allows us to consider the ego-motion of the LiDAR scanner while recording a single scan directly in the least squares adjustment. Furthermore, pruning the search space of correspondences and utilizing out-of-core circular buffer enables our approach to align thousands of point clouds efficiently. We successfully align point clouds recorded with a handheld LiDAR, as well as ones mounted on a vehicle, and are able to perform multi-session alignment. Copyright © 2024, The Authors. All rights reserved.

关键词： Continuous time systems

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：