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The increasing complexity of current real-time applications demands systems to make good use of the available computational resources. Guaranteeing timing behavior using traditional real-time scheduling policies is turning to be unfeasible, as these policies are based in pessimistic worst-case assumptions that pre-allocate resources even though they will be rarely used. The time-aware fault-tolerant (TAFT) scheduler presents a flexible scheduling strategy that allows the construction of schedules maximizing the CPU utilization. This work presents the use of the TAFT scheduler with computational intensive distributed embedded applications, in order to keep a high ratio of successful tasks completion and so guaranteeing its computational progress. More specifically, the paper sketches a "TAFT-based" fusion algorithm for laser-scanner data and derives the requirements that the execution of this algorithm has on the CPU-scheduling.