Bruno Lacerda

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—We present a methodology to build a Petri net realization of a supervisor that, given a Petri net model of a (multi-)robot system and a linear temporal logic (LTL) specification , forces the system to fulfil the specification. The methodology includes composing the Petri net model with the B ¨ uchi automaton representing the LTL formula and trimming the(More)
— We present a method to specify tasks and synthe-sise cost-optimal policies for Markov decision processes using co-safe linear temporal logic. Our approach incorporates a dynamic task handling procedure which allows for the addition of new tasks during execution and provides the ability to re-plan an optimal policy on-the-fly. This new policy minimises the(More)
In this paper, we use LTL to specify acceptable/desirable behaviours for a system modelled as a Petri net, and create a Petri net realization of a supervisor that is guaranteed to enforce them, by appropriately restricting the uncontrolled behaviour of the system.We illustrate the method with an application to the specification of coordination requirements(More)
— In planning for deliberation or navigation in real-world robotic systems, one of the big challenges is to cope with change. It lies in the nature of planning that it has to make assumptions about the future state of the world, and the robot's chances of successively accomplishing actions in this future. Hence, a robot's plan can only be as good as its(More)
We present a method to calculate cost-optimal policies for task specifications in co-safe linear temporal logic over a Markov decision process model of a stochastic system. Our key contribution is to address scenarios in which the task may not be achievable with probability one. We formalise a task progression metric and, using multi-objective probabilistic(More)
We introduce a plan specification method for robotic tasks modelled by finite state automata. Each state of a system composed of (multiple) robot(s) situated in an environment is described by a set of propositional symbols. Events associated to transitions drive the state dynamics and represent actions issued by the robot controller or uncontrollable events(More)
Thanks to the efforts of our community, autonomous robots are becoming capable of ever more complex and impressive feats. There is also an increasing demand for, perhaps even an expectation of, autonomous capabilities from end-users. However, much research into autonomous robots rarely makes it past the stage of a demonstration or experimental system in a(More)
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