Author name cluster

Pedro Lima

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

7 papers

1 author row

AIIM Journal 2019 Journal Article

Project INSIDE: towards autonomous semi-unstructured human–robot social interaction in autism therapy

Francisco S. Melo
Alberto Sardinha
David Belo
Marta Couto
Miguel Faria
Anabela Farias
Hugo Gambôa
Cátia Jesus

This paper describes the INSIDE system, a networked robot system designed to allow the use of mobile robots as active players in the therapy of children with autism spectrum disorders (ASD). While a significant volume of work has explored the impact of robots in ASD therapy, most such work comprises remotely operated robots and/or well-structured interaction dynamics. In contrast, the INSIDE system allows for complex, semi-unstructured interaction in ASD therapy while featuring a fully autonomous robot. In this paper we describe the hardware and software infrastructure that supports such rich form of interaction, as well as the design methodology that guided the development of the INSIDE system. We also present some results on the use of our system both in pilot and in a long-term study comprising multiple therapy sessions with children at Hospital Garcia de Orta, in Portugal, highlighting the robustness and autonomy of the system as a whole.

Details DOI

AAAI Conference 2014 Conference Paper

Point-Based POMDP Solving with Factored Value Function Approximation

Tiago Veiga
Matthijs Spaan
Pedro Lima

Partially observable Markov decision processes (POMDPs) provide a principled mathematical framework for modeling autonomous decision-making problems. A POMDP solution is often represented by a value function comprised of a set of vectors. In the case of factored models, the size of these vectors grows exponentially with the number of state factors, leading to scalability issues. We consider an approximate value function representation based on a linear combination of basis functions. In particular, we present a backup operator that can be used in any point-based POMDP solver. Furthermore, we show how under certain conditions independence between observation factors can be exploited for large computational gains. We experimentally verify our contributions and show that they have the potential to improve point-based methods in policy quality and solution size.

PDF Details

AAAI Conference 2013 Conference Paper

GSMDPs for Multi-Robot Sequential Decision-Making

João Messias
Matthijs Spaan
Pedro Lima

Markov Decision Processes (MDPs) provide an extensive theoretical background for problems of decision-making under uncertainty. In order to maintain computational tractability, however, real-world problems are typically discretized in states and actions as well as in time. Assuming synchronous state transitions and actions at ﬁxed rates may result in models which are not strictly Markovian, or where agents are forced to idle between actions, losing their ability to react to sudden changes in the environment. In this work, we explore the application of Generalized Semi-Markov Decision Processes (GSMDPs) to a realistic multi-robot scenario. A case study will be presented in the domain of cooperative robotics, where real-time reactivity must be preserved, and synchronous discrete-time approaches are therefore suboptimal. This case study is tested on a team of real robots, and also in realistic simulation. By allowing asynchronous events to be modeled over continuous time, the GSMDP approach is shown to provide greater solution quality than its discretetime counterparts, while still being approximately solvable by existing methods.

PDF Details

NeurIPS Conference 2011 Conference Paper

Efficient Offline Communication Policies for Factored Multiagent POMDPs

João Messias
Matthijs Spaan
Pedro Lima

Factored Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs) form a powerful framework for multiagent planning under uncertainty, but optimal solutions require a rigid history-based policy representation. In this paper we allow inter-agent communication which turns the problem in a centralized Multiagent POMDP (MPOMDP). We map belief distributions over state factors to an agent's local actions by exploiting structure in the joint MPOMDP policy. The key point is that when sparse dependencies between the agents' decisions exist, often the belief over its local state factors is sufficient for an agent to unequivocally identify the optimal action, and communication can be avoided. We formalize these notions by casting the problem into convex optimization form, and present experimental results illustrating the savings in communication that we can obtain.

PDF Details

AAMAS Conference 2010 Conference Paper

Coordination Through Institutional Roles in Robot Collectives

Jos
eacute; Nuno Pereira
Anders Christensen
Porf
iacute; rio Silva
Pedro Lima

In this paper, we demonstrate the benefit of role allocationin a collective of autonomous robots performing a simpletransport task. We demonstrate that, under certain conditions, the performance of the collective can be improvedwhen a subset of the robots assume institutional roles as traffic regulators. The concept of institutional roles is part of ahigh-level approach to the control of multi-robot collectivescalled Institutional Robotics. We compare the institutionalrobotics approach to a swarm robotics approach. Based onresults of experiments in simulation, we conclude that thecoordination provided by the traffic regulating robots improves performance for large collectives, but for small collectives the performance is higher when all robots are directlyinvolved in carrying out the task.

PDF

AAMAS Conference 2008 Conference Paper

Modelling, Analysis and Execution of Multi-Robot Tasks using Petri Nets

Hugo Costelha
Pedro Lima

This paper introduces Petri net (PN) based models of cooperative robotic tasks, namely those involving the coordination of two or more robots, thus requiring the exchange of synchronisation messages, either using explicit (e. g. , wireless) or implicit (e. g. , vision-based observation of teammates) communication. In the models, PN places represent primitive actions, subtasks and predicates set by sensor readings and communicated messages. Events are associated to PN transitions. The PN models can be used for task planning, plan execution and plan analysis. Di erent PN views enable the analysis of di erent properties. In this work we focus on plan analysis, namely on properties such as boundedness and liveness, corresponding to checking if resources usage is stable and plans have no deadlocks, as well as on stochastic performance, concerning the plan success probability. One novel feature of our work is that the analysis consists of composing several small action PN models with environment PN models, leading to a closed loop robot team/environment analysis methodology. Examples of application to simulated robotic soccer scenarios are presented.

PDF

AAMAS Conference 2008 Conference Paper

openSDK - An Open-source Implementation of OPEN-R

Nuno Lopes
Pedro Lima

This paper des ribes openSDK, an open-sour e implementation of Sony's AIBO development kit (OPEN-R). openSDK is apable of running unmodi ed AIBO programs (only a re ompilation is ne essary) on a standard omputer, using a simulator at full frame rate ( urrently only USARSim is supported) or on a di erent roboti hardware platform. openSDK also o ers standard debugging fa ilities for AIBO programs.

PDF