Privacy-Aware UAV Flights through Self-Configuring Motion Planning

During flights, an unmanned aerial vehicle (UAV) may not be allowed to move across certain areas due to soft constraints such as privacy restrictions. Current methods on self-adaption focus mostly on motion planning such that the trajectory does not trespass predetermined restricted areas. When the environment is cluttered with uncertain obstacles, however, these motion planning algorithms are not flexible enough to find a trajectory that satisfies additional privacy-preserving requirements within a tight time budget during the flights. In this paper, we propose a privacy risk aware motion planning method through the reconfiguration of privacy-sensitive sensors. It minimises environmental impact by re-configuring the sensor during flight, while still guaranteeing the hard safety and energy constraints such as collision avoidance and timeliness. First, we formulate a model for assessing privacy risks of dynamically detected restricted areas. In case the UAV cannot find a feasible solution to satisfy both hard and soft constraints from the current configuration, our decision making method can then produce an optimal reconfiguration of the privacy-sensitive sensor with a more efficient trajectory. We evaluate the proposal through various simulations with different settings in a virtual environment and also validate the approach through real test flights on DJI Matrice 100 UAV

MROS: Runtime Adaptation For Robot Control Architectures

Known attempts to build autonomous robots rely on complex control architectures, often implemented with the Robot Operating System platform (ROS). Runtime adaptation is needed in these systems, to cope with component failures and with contingencies arising from dynamic environments-otherwise, these affect the reliability and quality of the mission execution. Existing proposals on how to build self-adaptive systems in robotics usually require a major re-design of the control architecture and rely on complex tools unfamiliar to the robotics community. Moreover, they are hard to reuse across applications. This paper presents MROS: a model-based framework for run-time adaptation of robot control architectures based on ROS. MROS uses a combination of domain-specific languages to model architectural variants and captures mission quality concerns, and an ontology-based implementation of the MAPE-K and meta-control visions for run-time adaptation. The experiment results obtained applying MROS in two realistic ROS-based robotic demonstrators show the benefits of our approach in terms of the quality of the mission execution, and MROS' extensibility and re-usability across robotic applications

How do you architect your robots?:State of the practice and guidelines for ros-based systems

The Robot Operating System (ROS) is the de-facto standard for robotic software. If on one hand ROS is helping roboticists, e.g., by providing a standardized communication platform, on the other hand ROS-based systems are getting larger and more complex and could benefit from good software architecture practices. This paper presents an observational study aimed at (i) unveiling the state-ofthe- practice for architecting ROS-based systems and (ii) providing guidance to roboticists about how to properly architect ROS-based systems. To achieve these goals, we (i) build a dataset of 335 GitHub repositories containing real open-source ROS-based systems, (ii) mine the repositories for extracting the state of the practice about how roboticists are architecting them, and (iii) synthesize a catalog of 49 evidence-based guidelines for architecting ROS-based systems. The guidelines have been validated by 77 roboticists working on real-world open-source ROS-based systems

Socio-Cyber-Physical Systems: Models, Opportunities, Open Challenges

Almost without exception, cyber-physical systems operate alongside, for the benefit of, and supported by humans. Unsurprisingly, disregarding their social aspects during development and operation renders these systems ineffective. In this paper, we explore approaches to modelling and reasoning about the human involvement in socio-cyber-physical systems (SCPS). To provide an unbiased perspective, we describe both the opportunities afforded by the presence of human agents, and the challenges associated with ensuring that their modelling is sufficiently accurate to support decision making during SCPS development and, if applicable, at run-time. Using SCPS examples from emergency management and assisted living, we illustrate how recent advances in stochastic modelling, analysis and synthesis can be used to exploit human observations about the impact of natural and man-made disasters, and to support the efficient provision of assistive care

Advantages of Model-Based Development in terms of Business Benefits

Today’s industries require quick reactions and high-quality solutions. Businesses want to keep costs and resource misuse to a minimum for greater benefits. Automated processes can suit the efficiency needed in businesses. In the software field, this means quick development time and maintainability. Different methods have advantages towards these goals. One of these methods is model-based development. This thesis analyses model-based development as the method emphasises automation effi-ciency and high quality. Model-based development is based on capturing required elements in-to a model. The model is processed with appropriate tools to form a wanted outcome. The tools tend to be highly automatic. The approach is applied in different development fields, more with practical simpler systems than complex software. The simpler ones usually have functional behaviour that can be modelled easier. This thesis includes multiple advantages of a model-based approach that can answer the needs and requirements of industries, even overcome them. Advantages like reduced development time with high quality and model reusability can result in business-level benefits. To exploit the benefits in today’s state requires costs and effort as they are many times needed to be performed in a specific environment and with specific tools. The environment sets the need for specific knowledge of practises and effort in understanding the method to succeed. The challenges are needed to be overcome by more generally applicable solutions. The analysing of the advantages in this thesis shows that there is no significant benefit that can be achieved through model-based development. The benefits are due to the overall advantageous nature of the approach. While the commercial usage of the model-based development is still narrow, there is a future for the methodology. Research regarding model-based development is refining the used concepts and providing new ways to exploit the advantages