On-orbit construction and maintenance technology will play a significant role in future space exploration.The dexterous multifunctional spacecraft equipped with multi-arm,for instance,Spider Fab Bot,has attracted a gr...On-orbit construction and maintenance technology will play a significant role in future space exploration.The dexterous multifunctional spacecraft equipped with multi-arm,for instance,Spider Fab Bot,has attracted a great deal of focus due to its versatility in completing these missions.In such engineering practice,point-to-point moving in a complex environment is the fundamental issue.This paper investigates the three-dimensional point-to-point path planning problem,and a hierarchical path planning architecture is developed to give the trajectory of the multi-arm spacecraft effectively and efficiently.In the proposed 3-level architecture,the high-level planner generates the global constrained centric trajectory of the spacecraft with a rigid envelop assumption;the middle-level planner contributes the action sequence,a combination of the newly developed general translational and rotational locomotion mode,to cope with the relative position and attitude of the arms about the centroid of the spacecraft;the low-level planner maps the position/attitude of the end-effector of each arm from the operational space to the joint space optimally.Finally,the simulation experiment is carried out,and the results verify the effectiveness of the proposed three-layer architecture path planning strategy.展开更多
Document-level machine translation(MT)remains challenging due to its difficulty in efficiently using documentlevel global context for translation.In this paper,we propose a hierarchical model to learn the global conte...Document-level machine translation(MT)remains challenging due to its difficulty in efficiently using documentlevel global context for translation.In this paper,we propose a hierarchical model to learn the global context for documentlevel neural machine translation(NMT).This is done through a sentence encoder to capture intra-sentence dependencies and a document encoder to model document-level inter-sentence consistency and coherence.With this hierarchical architecture,we feedback the extracted document-level global context to each word in a top-down fashion to distinguish different translations of a word according to its specific surrounding context.Notably,we explore the effect of three popular attention functions during the information backward-distribution phase to take a deep look into the global context information distribution of our model.In addition,since large-scale in-domain document-level parallel corpora are usually unavailable,we use a two-step training strategy to take advantage of a large-scale corpus with out-of-domain parallel sentence pairs and a small-scale corpus with in-domain parallel document pairs to achieve the domain adaptability.Experimental results of our model on Chinese-English and English-German corpora significantly improve the Transformer baseline by 4.5 BLEU points on average which demonstrates the effectiveness of our proposed hierarchical model in document-level NMT.展开更多
本文描述了一个基于分层语块分析的统计翻译模型。该模型在形式上不仅符合同步上下文无关文法,而且融合了基于条件随机场的英文语块分析知识,因此基于分层语块分析的统计翻译模型做到了将句法翻译模型和短语翻译模型有效地结合。该系统...本文描述了一个基于分层语块分析的统计翻译模型。该模型在形式上不仅符合同步上下文无关文法,而且融合了基于条件随机场的英文语块分析知识,因此基于分层语块分析的统计翻译模型做到了将句法翻译模型和短语翻译模型有效地结合。该系统的解码算法改进了线图分析的CKY算法,融入了线性的N-gram语言模型。目前,本文主要针对中文-英文的口语翻译进行了一系列实验,并以国际口语评测IWSLT(International Workshopon Spoken Language Translation)为标准,在2005年的评测测试集上,BLEU和NIST得分均比统计短语翻译系统有所提高。展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.62003115 and 11972130)the Shenzhen Natural Science Fund(the Stable Support Plan Program GXWD2020123015542700320200821170719001)。
文摘On-orbit construction and maintenance technology will play a significant role in future space exploration.The dexterous multifunctional spacecraft equipped with multi-arm,for instance,Spider Fab Bot,has attracted a great deal of focus due to its versatility in completing these missions.In such engineering practice,point-to-point moving in a complex environment is the fundamental issue.This paper investigates the three-dimensional point-to-point path planning problem,and a hierarchical path planning architecture is developed to give the trajectory of the multi-arm spacecraft effectively and efficiently.In the proposed 3-level architecture,the high-level planner generates the global constrained centric trajectory of the spacecraft with a rigid envelop assumption;the middle-level planner contributes the action sequence,a combination of the newly developed general translational and rotational locomotion mode,to cope with the relative position and attitude of the arms about the centroid of the spacecraft;the low-level planner maps the position/attitude of the end-effector of each arm from the operational space to the joint space optimally.Finally,the simulation experiment is carried out,and the results verify the effectiveness of the proposed three-layer architecture path planning strategy.
基金supported by the National Natural Science Foundation of China under Grant Nos.61751206,61673290 and 61876118the Postgraduate Research&Practice Innovation Program of Jiangsu Province of China under Grant No.KYCX20_2669a project funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD).
文摘Document-level machine translation(MT)remains challenging due to its difficulty in efficiently using documentlevel global context for translation.In this paper,we propose a hierarchical model to learn the global context for documentlevel neural machine translation(NMT).This is done through a sentence encoder to capture intra-sentence dependencies and a document encoder to model document-level inter-sentence consistency and coherence.With this hierarchical architecture,we feedback the extracted document-level global context to each word in a top-down fashion to distinguish different translations of a word according to its specific surrounding context.Notably,we explore the effect of three popular attention functions during the information backward-distribution phase to take a deep look into the global context information distribution of our model.In addition,since large-scale in-domain document-level parallel corpora are usually unavailable,we use a two-step training strategy to take advantage of a large-scale corpus with out-of-domain parallel sentence pairs and a small-scale corpus with in-domain parallel document pairs to achieve the domain adaptability.Experimental results of our model on Chinese-English and English-German corpora significantly improve the Transformer baseline by 4.5 BLEU points on average which demonstrates the effectiveness of our proposed hierarchical model in document-level NMT.
文摘本文描述了一个基于分层语块分析的统计翻译模型。该模型在形式上不仅符合同步上下文无关文法,而且融合了基于条件随机场的英文语块分析知识,因此基于分层语块分析的统计翻译模型做到了将句法翻译模型和短语翻译模型有效地结合。该系统的解码算法改进了线图分析的CKY算法,融入了线性的N-gram语言模型。目前,本文主要针对中文-英文的口语翻译进行了一系列实验,并以国际口语评测IWSLT(International Workshopon Spoken Language Translation)为标准,在2005年的评测测试集上,BLEU和NIST得分均比统计短语翻译系统有所提高。
