Bruno Lacerda

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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)
We present a method to specify tasks and synthesise 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 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)
Thanks to the efforts of the robotics and autonomous systems community, the myriad applications and capacities of robots are ever increasing. There is increasing demand from end users for autonomous service robots that can operate in real environments for extended periods. In the Spatiotemporal Representations and Activities for Cognitive Control in(More)
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 Büchi automaton representing the LTL formula and trimming the result(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)
We present a decentralized methodology to control multi-robot systems, where each robot behaviour is modelled as a Petri net (PN) and a set of coordination rules between the robots is given as linear temporal logic (LTL) formulas describing safety properties for the system. The LTL formulas are used to define the events and changes in state that must be(More)