31 research outputs found
Robot Teams for Multi-Objective Tasks
No full textArtificial Intelligence research has developed, during the last fifty years, a large variety
of tools aimed at establishing rational behaviors for cognitive entities, called
agents. This dissertation addresses the problem of producing rational behaviors for
a team of agents pursuing possibly different objectives. The problem can be decomposed
into the following two research issues: i) multi-agent behavior and execution
modelling, and, ii) multi-objective problem solving. Our resarch focus on multi-agent
systems has been modelling distributed execution of asynchronous plans composed
of actions of uncertain duration, possibly coordinated through direct communication.
The distributed execution and the communication costs require to model the dynamics
of knowledge when asynchronously distributed in the system under the effect of
local and communication actions. The second research focus of this thesis, has been
multi-objective problem solving. The introduction of multiple objectives in planning
domains, allows us to generalize classical multi-agent planning, thus augmenting the
class of solvable problems. Multi-objective formulations allow an incomplete, and
possibly contradictory, description of goals, and are frequent in many practical applications.
For example, consider the case where requests to a system come from a
large community of users or from the members of a research group studying different
aspects of a complex problem.
This thesis provides three main contributions. The first contribution consists of
two formal tools for modelling multi-agent systems. One, for planning, and, one, for
distributed execution. Each model defines a class of languages based on single-agent
action languages and Petri nets, respectively. The second contribution addresses two
multi-objective issues: solution concept and solving techniques. First, we define a
novel solution concept which is, to our knowledge, the first refinement of Pareto optimality
for any multi-objective problem. Second, we provide a sound and complete
algorithm for solving it. Finally, the third contribution is a case study on the Urban
Search And Rescue (USAR) robotic problem, presented in three formulations of increasing
complexity. USAR, in its classical formulation, is a multi-objective problem
where the objectives are: exploration, mapping, and victim detection
A Probabilistic Action Duration Model for Plan Selection and Monitoring
No full textThe execution of tasks for a robotic agent embedded in a dynamic environment brings about several challenges, due to unpredictable (or unobservable) events, and to inaccurate perception. Moreover, the agent can perform multiple tasks and each task can be achieved by applying different plans, therefore the decision about which strategy is the most convenient, given the current situation of the world, is important for assessing an intelligent overall behavior of the agent. This paper tackles the problem of on-line execution monitoring in a novel way with respect to previous work, since: 1) it considers uncertainty in the duration of actions with a probabilistic model of action duration; 2) it evaluates the cost of each possible plan at run-time in terms of probability of successful termination within a desired expected time. The approach has been evaluated both in a robotic soccer and a surveillance scenario
Assignment of Dynamically Perceived Tasks by Token Passing In Multi-Robot Systems
No full textThe problem of assigning tasks to a group of robots acting in a dynamic environment is a fundamental issue for a Multi Robot System (MRS) and several techniques have been studied to address this problem. Such techniques usually rely on the assumption that tasks to be assigned are inserted into the system in a coherent fashion. In this work we consider a scenario where tasks to be accomplished are perceived by the robots during mission execution. This issu
Teamwork Design Based on Petri Net Plans
No full textThis paper presents a design of cooperative behaviors through Petri Net Plans, based on the principles provided by Cohen and Levesque's Joint Commitments Theory. Petri Net Plans are a formal tool that has proved very effective for the representation of multi-robot plans, providing all the means necessary for the design of cooperation. The Joint Commitment theory is used as a guideline to present a general multi-robot Petri Net Plan for teamwork, that can be used to model a wide range of cooperative behaviors. As an example we describe the implementation of a robotic-soccer passing task, performed by Sony AIBO robots. © 2009 Springer Berlin Heidelberg
Context-based design of robotic systems
No full textThe need for improving the robustness, as well as the ability to adapt to different operational conditions, is a key requirement for a wider deployment of robots in many application domains. In this paper, we present an approach to the design of robotic systems, that is based on the explicit representation of knowledge about context. The goal of the approach is to improve the system's performance, by dynamically tailoring the functionalities of the robot to the specific features of the situation at hand. While the idea of using contextual knowledge is not new, the proposed approach generalizes previous work, and its advantages are discussed through a case study including several experiments. In particular, we identify many attempts to use contextual knowledge in several basic functionalities of a mobile robot such as: behavior, navigation, exploration, localization, mapping and perception. We then show how re-designing our mobile platform with a common representation of contextual knowledge, leads to interesting improvements in many of the above mentioned components, thus achieving greater flexibility and robustness in the face of different situations. Moreover, a clear separation of contextual knowledge leads to a design methodology, which supports the design of small specialized system components instead of complex self-contained subsystems. © 2008 Elsevier B.V. All rights reserved
RFID-Based Exploration for Large Robot Teams
No full textTo coordinate a team of robots for exploration is a challenging problem, particularly in large areas as for example the devastated area after a disaster. This problem can generally be decomposed into task assignment and multi-robot path planning. In this paper, we address both problems jointly. This is possible because we reduce significantly the size of the search space by utilizing RFID tags as coordination points. The exploration approach consists of two parts: a stand-alone distributed local search and a global monitoring process which can be used to restart the local search in more convenient locations. Our results show that the local exploration works for large robot teams, particularly if there are limited computational resources. Experiments with the global approach showed that the number of conflicts can be reduced, and that the global coordination mechanism increases significantly the explored area.Artificial Intelligence & Integrated Computer System
Petri Net Plans A framework for collaboration and coordination in multi-robot systems
No full textProgramming the behavior of multi-robot systems is a challenging task which has a key role in developing effective systems in many application domains. In this paper, we present Petri Net Plans (PNPs), a language based on Petri Nets (PNs), which allows for intuitive and effective robot and multi-robot behavior design. PNPs are very expressive and support a rich set of features that are critical to develop robotic applications, including sensing, interrupts and concurrency. As a central feature, PNPs allow for a formal analysis of plans based on standard PN tools. Moreover, PNPs are suitable for modeling multi-robot systems and the developed behaviors can be executed in a distributed setting, while preserving the properties of the modeled system. PNPs have been deployed in several robotic platforms in different application domains. In this paper, we report three case studies, which address complex single robot plans, coordination and collaboration
Petri net plans: a formal model for representation and execution of multi-robot plans
No full textThe aim of this paper is to describe a novel representation framework for high level robot and multi-robot programming, called Petri Net Plans (PNP), that allows for representing all the action features that are needed for describing complex plans in dynamic environments. We provide a sound and complete execution algorithm for PNPs based on the semantics of Petri nets. Moreover, we show that multi-robot PNPs allow for a sound and complete distributed execution algorithm, given that a reliable communication channel is provided. PNPs have been used for describing effective plans for actual robotic agents which inhabit dynamic, partially observable and unpredictable environments, and experimented in different application scenarios. Copyright © 2008, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved
