Time varying environments or model selection problems lead to crucial dilemmas in identification and control science. In this paper, we propose a modular prediction scheme consisti...
Modular robots are systems composed of a number of independent units that can be reconfigured to fit the task at hand. When the modules are computationally independent, they for...
Zack J. Butler, Robert Fitch, Daniela Rus, Yuhang ...
This paper introduces the RL-TOPs architecture for robot learning, a hybrid system combining teleo-reactive planning and reinforcement learning techniques. The aim of this system ...
In previous work we have shown how modular code can be automatically generated from a synchronous block diagram notation where all blocks fire at all times. Here, we extend this ...
Safe and tight worst-case execution times (WCETs) are important when scheduling hard realtime systems. This paper presents METAMOC, a modular method, based on model checking and s...
Andreas E. Dalsgaard, Mads Chr. Olesen, Martin Tof...