In this paper, the TAS-I （Thales Alenia Space-Italy） Test Bench for Robotics and Autonomy （TBRA） is presented. It is based on a flexible and modular software architecture （Framework Engine）, in which each functi...In this paper, the TAS-I （Thales Alenia Space-Italy） Test Bench for Robotics and Autonomy （TBRA） is presented. It is based on a flexible and modular software architecture （Framework Engine）, in which each functional module （representing the GNC subsystems） implements a key functionality of the GNC （Guidance Navigation and Control）. Modules communicate by means of standardised interfaces designed for exchange of necessary information among the modules composing the entire system. This approach permits the interchange-ability of each subsystem without affecting the overall functionalities of the GNC system. In this paper, the TBRA system, together with the implemented functional modules will be described. Tests results will be reported and future development will be discussed.展开更多
With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:e...With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.展开更多
Efficient support for querying large-scale resource description framework （RDF） triples plays an important role in semantic web data management. This paper presents an efficient RDF query engine to evaluate SPARQL q...Efficient support for querying large-scale resource description framework （RDF） triples plays an important role in semantic web data management. This paper presents an efficient RDF query engine to evaluate SPARQL queries, where the inverted index structure is employed for indexing the RDF triples. A set of operators on the inverted index was developed for query optimization and evaluation. Then a main-tree-shaped optimization algorithm was developed that transforms a SPARQL query graph into the op-timal query plan by effectively reducing the search space to determine the optimal joining order. The opti-mization collects a set of RDF statistics for estimating the execution cost of the query plan. Finally the opti-mal query plan is evaluated using the defined operators for answering the given SPARQL query. Extensive tests were conducted on both synthetic and real datasets containing up to 100 million triples to evaluate this approach with the results showing that this approach can answer most queries within 1 s and is extremely efficient and scalable in comparison with previous best state-of-the-art RDF stores.展开更多
文摘In this paper, the TAS-I （Thales Alenia Space-Italy） Test Bench for Robotics and Autonomy （TBRA） is presented. It is based on a flexible and modular software architecture （Framework Engine）, in which each functional module （representing the GNC subsystems） implements a key functionality of the GNC （Guidance Navigation and Control）. Modules communicate by means of standardised interfaces designed for exchange of necessary information among the modules composing the entire system. This approach permits the interchange-ability of each subsystem without affecting the overall functionalities of the GNC system. In this paper, the TBRA system, together with the implemented functional modules will be described. Tests results will be reported and future development will be discussed.
基金supported by the National Key Research and Development Program of China“Comprehensive Application Demonstration of Self-developed BIM Platform in the Full Life Cycle of Engineering Construction”(Grant No.2024YFC3809700)。
文摘With extensive application of building information modeling(BIM),vast BIM model resources have accumulated from both new and existing projects.Digital twins,a key application of these models,face two main challenges:exponential growth in geometric and attribute data,risking data explosion,and low data utilization due to insufficient semantic association among multi-source data across projects and domains.This paper addresses the challenge of reducing system complexity via scenario-driven methods while achieving deep semantic integration of cross-domain BIM data.It proposes an ontology-based“Digital Theater”framework that defines data boundaries based on scenario requirements and employs dynamic trimming strategies to reduce complexity.By combining a simplified data standard with a multi-domain fusion ontology model,the framework constructs scenario-based data integration rules for semantic alignment.An adaptive relational database with object storage design further supports efficient engineering data storage and utilization.The proposed method significantly reduces the complexity of data processing,enabling the integrated application of multi-domain data at a lower cost while enhancing the decision-support capabilities of BIM data.This framework demonstrates potential for application in diverse scenarios,supporting engineering digitalization and smart city development.
基金Supported by the Shanghai Jiao Tong University and IBM CRL Joint Project
文摘Efficient support for querying large-scale resource description framework （RDF） triples plays an important role in semantic web data management. This paper presents an efficient RDF query engine to evaluate SPARQL queries, where the inverted index structure is employed for indexing the RDF triples. A set of operators on the inverted index was developed for query optimization and evaluation. Then a main-tree-shaped optimization algorithm was developed that transforms a SPARQL query graph into the op-timal query plan by effectively reducing the search space to determine the optimal joining order. The opti-mization collects a set of RDF statistics for estimating the execution cost of the query plan. Finally the opti-mal query plan is evaluated using the defined operators for answering the given SPARQL query. Extensive tests were conducted on both synthetic and real datasets containing up to 100 million triples to evaluate this approach with the results showing that this approach can answer most queries within 1 s and is extremely efficient and scalable in comparison with previous best state-of-the-art RDF stores.
