A5048898358- Formal Methods in Verification
- Real-Time Systems Scheduling
- Advanced Software Engineering Methodologies
- AI-based Problem Solving and Planning
- Robotic Path Planning Algorithms
- Logic, programming, and type systems
- Modular Robots and Swarm Intelligence
- Distributed systems and fault tolerance
- Model-Driven Software Engineering Techniques
- Simulation Techniques and Applications
- Human-Automation Interaction and Safety
- Service-Oriented Architecture and Web Services
- Petri Nets in System Modeling
Universidad Nacional de Cuyo
2020-2023
Balseiro Institute
2020-2023
The Human Machine Teaming (HMT) paradigm focuses on supporting partnerships between humans and autonomous machines. HMT describes requirements for transparency, augmented cognition, coordination that enable far richer than those found in typical human-on-the-loop human-in-the-loop systems. Autonomous, self-adaptive systems domains such as driving, robotics, Cyber-Physical Systems, are often implemented using the MAPE-K feedback loop primary reference model. However, while enables fully...
Temporal task planning guarantees a robot will succeed in its as long certain explicit and implicit assumptions about the robot's operating environment, sensors, capabilities hold. A executing plan can silently fail to fulfill if are violated at runtime. Monitoring assumption violations runtime flag silent failures also provide mitigation remediation opportunities. However, this requires means for describing combining temporal quantitative data, automatic construction of correct monitors...
Temporal logic task planning for robotic systems suffers from state explosion when specifications involve large numbers of discrete locations. We provide a novel approach, particularly suited with universally quantified locations, that has constant time respect to the number enabling synthesis plans an arbitrary them. propose hybrid control framework uses iterator manage discretised workspace hiding it plan enacted by event controller. A downside our approach is incurs in increased overhead...
The design of systems that can change their behaviour to account for scenarios were not foreseen at time remains an open challenge. In this paper we propose approach adaptation mobile robot missions is constrained a predefined set mission evolutions. We applying the MORPH adaptive software architecture UAVs and show how controller synthesis be used both guarantee correct transitioning from old new goals while architectural reconfiguration include actuators sensors if necessary. brings...
Recent robotic research has led to different architectural approaches that support enactment of automatically synthesized discrete event controllers from user specifications over low-level continuous variable controllers. Simulation these hybrid control robotics can be a useful validation tool for robot users and architecture designers, but presents the key challenge working with representations robot, its environment mission plans. In this work we address showcasing unified DEVS-based...
Robotic research over the last decades have lead us to different architectures automatically synthesise discrete event controllers and implement these motion task plans in real-world robot scenarios. However, usually build on existing hardware, generating as a result solutions that are influenced and/or restricted their design by available capabilities sensors. In contrast approaches, we propose methodology that, given specific domain of application, allowed first end-to-end implementation...
Temporal logic task planning for robotic systems suffers from state explosion when specifications involve large numbers of discrete locations. We provide a novel approach, particularly suited tasks with universally quantified locations, that has constant time respect to the number enabling synthesis plans an arbitrary them. propose hybrid control framework uses iterator manage discretised workspace hiding it plan enacted by event controller. A downside our approach is incurs in increased...