Real time systems must respect their temporal constraints both in nominal and degraded conditions. Environment disturbances cause faults which are revealed by errors during task execution. Therefore, schedulers must be fault tolerant to guarantee no missed deadline. Phenomena like electromagnetic fields disturb real-time systems on a extended period of time. It is difficult to forecast faults and their consequences to build efficient faulttolerant systems. The classical fault models deal with pseudo-periodic faults. They are not made for phenomena extended in time. This paper intends to describe electromagnetic disturbances in a new fault model, named fault burst model. In adequation with the fault burst model, we provide error recovery strategies. Finally, we study the effects of strategies on the schedulability analysis to guarantee fault tolerance when fault bursts occur.

The integration of autonomous robots in real applications is a challenge. It needs that the behaviour of these robots is proved to be safe. In this paper, we focus on the real-time software embedded on the robot, and that supports the execution of safe and autonomous behaviours. We propose a methodology that goes from the design of component-based software architectures using a Domain Specific Language, to the analysis of the real-time constraints that arise when considering the safety of software applications. This methodology is supported by a code generation toolchain that ensures that the code eventually executed on the robot is consistent with the analysis performed. This methodology is applied on a ground robot exploring an area. Categories (2), (3)

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The development of software architectures that ensure both a high-level of autonomy in the mission, and the robustness to possible failures, is a challenging task. In this paper, we propose to structure the software architecture around a skill management layer, based on formal skill models. This skill management layer helps to structure and test the underlying functional layer, while it provides a simple abstraction to the decision layer. This architecture has been used to support the implementation of resilient behaviours, using Behaviour Trees, in autonomous UAV missions, when facing sensor failures or communication losses.

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