Hierarchical Software Architecture Research Articles

MATLAB-based simulation of industrial robots in water environment monitoring

Abstract The use of industrial robots based on MATLAB simulation for water environment monitoring is to monitor the water environment better, improve monitoring efficiency and reduce monitoring costs. The robot can better collect data and can engage in deeper water-specific information. In this paper, based on the discussion of the water environment monitoring robots used in countries around the world for water environment monitoring, we introduce a MATLAB-based simulation of industrial robots in a wide range of water environments to simulate the autonomous data acquisition system. The main advantages are: compared with other robots, it can realize the “wide range” of water environment data collection; compared with fixed buoys, it can realize the “autonomous” collection of water environment monitoring data and gives the autonomous collection process and hierarchical software progression. The autonomous acquisition process and hierarchical software architecture are presented. The simulation results analysis shows no difference between the simulated data and the predicted data from the historical data using MATLAB-based industrial robots for water environment monitoring. This shows that the development of industrial robot simulation in water environment monitoring is promising and feasible.

Highway Lane-Changing Prediction Using a Hierarchical Software Architecture based on Support Vector Machine and Continuous Hidden Markov Model

Highway Lane-Changing Prediction Using a Hierarchical Software Architecture based on Support Vector Machine and Continuous Hidden Markov Model

Ridon Vehicle: Drive-by-Wire System for Scaled Vehicle Platform and Its Application on Behavior Cloning

For autonomous driving research, using a scaled vehicle platform is a viable alternative compared to a full-scale vehicle. However, using embedded solutions such as small robotic platforms with differential driving or radio-controlled (RC) car-based platforms can be limiting on, for example, sensor package restrictions or computing challenges. Furthermore, for a given controller, specialized expertise and abilities are necessary. To address such problems, this paper proposes a feasible solution, the Ridon vehicle, which is a spacious ride-on automobile with high-driving electric power and a custom-designed drive-by-wire system powered by a full-scale machine-learning-ready computer. The major objective of this paper is to provide a thorough and appropriate method for constructing a cost-effective platform with a drive-by-wire system and sensor packages so that machine-learning-based algorithms can be tested and deployed on a scaled vehicle. The proposed platform employs a modular and hierarchical software architecture, with microcontroller programs handling the low-level motor controls and a graphics processing unit (GPU)-powered laptop computer processing the higher and more sophisticated algorithms. The Ridon vehicle platform is validated by employing it in a deep-learning-based behavioral cloning study. The suggested platform’s affordability and adaptability would benefit broader research and the education community.

A new hierarchical software architecture towards safety-critical aspects of a drone system

A new hierarchical software architecture is proposed to improve the safety and reliability of a safety-critical drone system from the perspective of its source code. The proposed architecture uses formal verification methods to ensure that the implementation of each module satisfies its expected design specification, so that it prevents a drone from crashing due to unexpected software failures. This study builds on top of a formally verified operating system kernel, certified kit operating system (CertiKOS). Since device drivers are considered the most important parts affecting the safety of the drone system, we focus mainly on verifying bus drivers such as the serial peripheral interface and the inter-integrated circuit drivers in a drone system using a rigorous formal verification method. Experiments have been carried out to demonstrate the improvement in reliability in case of device anomalies.

SambotII: A New Self-Assembly Modular Robot Platform Based on Sambot

A new self-assembly modular robot (SMR) SambotII is developed based on SambotI, which is a previously-built hybird type SMR that is capable of autonomous movement and self-assembly. As is known, SambotI only has limited abilities of environmental perception and target recognition, because its STM-32 processor cannot handle heavy work, like image processing and path planning. To improve the computing ability, an x86 dual-core CPU is applied and a hierarchical software architecture with five layers is designed. In addition, to enhance its perception abilities, a laser-camera unit and a LED-camera unit are employed to obtain the distance and angle information, respectively, and the color-changeable LED lights are used to identify different passive docking surfaces during the docking process. Finally, the performances of SambotII are verified by docking experiments.

Design and Realization of Control System for New Nuclear Fuel Elevator System

As one of the key equipment for handling nuclear assembly in nuclear power station, the Nuclear Fuel Elevator (NFE) is mainly used to handle the new assembly and examine the spent assembly. Considering the safety and reliability for the high radioactivity environment, the control system with two levels of hardware controllers and module hierarchical software architecture is proposed. The HMI which is convenient and user-friendly is also developed for operator. The load protection and dynamic PID-control is mentioned in detail.

Extraction and evolution of architectural variability models in plugin-based systems

Variability management is a key issue when building and evolving software-intensive systems, making it possible to extend, configure, customize and adapt such systems to customers' needs and specific deployment contexts. A wide form of variability can be found in extensible software systems, typically built on top of plugin-based architectures that offer a (large) number of configuration options through plugins. In an ideal world, a software architect should be able to generate a system variant on-demand, corresponding to a particular assembly of plugins. To this end, the variation points and constraints between architectural elements should be properly modeled and maintained over time (i.e., for each version of an architecture). A crucial, yet error-prone and time-consuming, task for a software architect is to build an accurate representation of the variability of an architecture, in order to prevent unsafe architectural variants and reach the highest possible level of flexibility. In this article, we propose a reverse engineering process for producing a variability model (i.e., a feature model) of a plugin-based architecture. We develop automated techniques to extract and combine different variability descriptions, including a hierarchical software architecture model, a plugin dependency model and the software architect knowledge. By computing and reasoning about differences between versions of architectural feature models, software architect can control both the variability extraction and evolution processes. The proposed approach has been applied to a representative, large-scale plugin-based system (FraSCAti), considering different versions of its architecture. We report on our experience in this context.

Design of Automatic Test Software for Electromagnetic Radiation Safety Margin

Focused on the current problems of the automated testing for electromagnetic compatibility, this paper proposes a hierarchical and modular electromagnetic compatibility software architecture based on the OOP. This paper gives the design ideas, methods and main features and develops a test automation software for electromagnetic radiation safety margin based on this architecture. Experimental results show this software improves test efficiency, accuracy and achieves the desired effect compared with the manual testing. This software also reduces the intensity of the work of the testers and has a good value in engineering.

Design and reliability analysis of DP-3 dynamic positioning control architecture

As the exploration and exploitation of oil and gas proliferate throughout deepwater area, the requirements on the reliability of dynamic positioning system become increasingly stringent. The control objective ensuring safety operation at deep water will not be met by a single controller for dynamic positioning. In order to increase the availability and reliability of dynamic positioning control system, the triple redundancy hardware and software control architectures were designed and developed according to the safe specifications of DP-3 classification notation for dynamically positioned ships and rigs. The hardware redundant configuration takes the form of triple-redundant hot standby configuration including three identical operator stations and three real-time control computers which connect each other through dual networks. The function of motion control and redundancy management of control computers were implemented by software on the real-time operating system VxWorks. The software realization of task loose synchronization, majority voting and fault detection were presented in details. A hierarchical software architecture was planed during the development of software, consisting of application layer, real-time layer and physical layer. The behavior of the DP-3 dynamic positioning control system was modeled by a Markov model to analyze its reliability. The effects of variation in parameters on the reliability measures were investigated. The time domain dynamic simulation was carried out on a deepwater drilling rig to prove the feasibility of the proposed control architecture.

First-Class Connectors to Support Systematic Construction of Hierarchical Software Architecture.

To provide hierarchical description from different software architectural view points we need more than one abstraction hierarchy and connection mechanisms to support the interactions among components. Also, these mechanisms will support the refinement and traceability of architectural elements through the different levels of each hierarchy. Current methods and tools provide poor support for the challenge posed by developing system using hierarchical description. This paper describes an architecture-centric approach allowing the user to describe the logical architecture view where a physical architecture view is generated automatically for all application instances of the logical architecture.

A new system architecture for crowd simulation

Crowd simulation requires both rendering visually plausible images and managing the behavior of autonomous agents. Therefore, these applications need an efficient design that allows them to simultaneously handle these two requirements. Although several proposals have focused on the software architectures for these systems, no proposals have focused on the computer systems supporting them. In this paper, we analyze the computer architectures used in the literature to support distributed virtual environments. Also, we propose a distributed computer architecture which is efficient enough to support simulations of thousand of autonomous agents. This proposal consists of a cluster of interconnected computers in order to improve flexibility and robustness, as well as a hierarchical software architecture that efficiently provides consistency. Performance evaluation results show that the trade-off between flexibility and consistency allows to efficiently manage thousands of autonomous agents. Therefore, this network-based system architecture can provide the required scalability for large-scale crowd simulations.

Real-Time Control Architecture for Sauvim

This paper provides an overview of hardware and software architecture of SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions) which has been developed at the Autonomous Systems Laboratory (ASL). Unlike other autonomous underwater vehicles (AUVs), SAUVIM is equipped with an electric motor-driven dexterous robotic manipulator for underwater tasks requiring physical contacts with underwater objects. The overall vehicle-manipulator system becomes a high degrees-of-freedom multi-body nonlinear dynamic system. To effectively control this complex robotic system, distributed real-time hardware architecture and modified hierarchical software architecture with Sensor Data Bus (SDB) were used. The SDB makes it possible to get a prompt response from high-level control with respect to low-level sensor data. SAUVIM Task Description Language (STDL) was also developed to increase the flexibility of the vehicle tasks. Using STDL, any modification of control software is not required for various tasks. The user can also easily describe a task with various sensor data and handle multiple actuators.

A modular integrated robot control system

The Modular Integrated Robot Control System (MIRCS) is a PC-based distributed control system for industrial robots. This system possesses expansibility and flexibility for the strict requirements of computation power and the complicated robot control. A host computer and several server computers constitute the hardware architecture of MIRCS. The host computer communicates with the other server computers in two ways: tight coupling by dual-port RAM and loose coupling by an Ethernet network. The hierarchical software architecture in MIRCS has several modules to make the system flexible and portable.