Integrating ASP into ROS for Reasoning in Robots

Andres, Benjamin; Rajaratnam, David; Sabuncu, Orkunt; Schaub, Torsten

doi:10.1007/978-3-319-23264-5_7

Cited by 13 publications

(9 citation statements)

References 12 publications

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“…Since its first release and accompanying publication (Gebser et al 2014), clingo's multi-shot solving framework has been used for implementing several ASP-based reasoning systems, such as asprin (Brewka et al 2015a;Brewka et al 2015b), aspic , rosoclingo (Andres et al 2015), and dflat (Abseher et al 2014); various forms of aggregates were implemented with it by and . As well, dlvhex (Eiter et al 2012) builds upon clingo and its versatile API.…”

Section: Resultsmentioning

confidence: 99%

Multi-shot ASP solving with clingo

Gebser

Kaminski

Kaufmann

et al. 2018

Theory and Practice of Logic Programming

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We introduce a new flexible paradigm of grounding and solving in Answer Set Programming (ASP), which we refer to as multi-shot ASP solving, and present its implementation in the ASP systemclingo. Multi-shot ASP solving features grounding and solving processes that deal with continuously changing logic programs. In doing so, they remain operative and accommodate changes in a seamless way. For instance, such processes allow for advanced forms of search, as in optimization or theory solving, or interaction with an environment, as in robotics or query answering. Common to them is that the problem specification evolves during the reasoning process, either because data or constraints are added, deleted, or replaced. This evolutionary aspect adds another dimension to ASP since it brings about state changing operations. We address this issue by providing an operational semantics that characterizes grounding and solving processes in multi-shot ASP solving. This characterization provides a semantic account of grounder and solver states along with the operations manipulating them. The operative nature of multi-shot solving avoids redundancies in relaunching grounder and solver programs and benefits from the solver's learning capacities.clingoaccomplishes this by complementing ASP's declarative input language with control capacities. On the declarative side, a new directive allows for structuring logic programs into named and parameterizable subprograms. The grounding and integration of these subprograms into the solving process is completely modular and fully controllable from the procedural side. To this end,clingooffers a new application programming interface that is conveniently accessible via scripting languages. By strictly separating logic and control,clingoalso abolishes the need for dedicated systems for incremental and reactive reasoning, likeiclingoandoclingo, respectively, and its flexibility goes well beyond the advanced yet still rigid solving processes of the latter.

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Section: Resultsmentioning

confidence: 99%

Multi-shot ASP solving with clingo

Gebser

Kaminski

Kaufmann

et al. 2018

Theory and Practice of Logic Programming

Self Cite

234

198

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“…In our setting, we employed (i) ALVAR, an AR tag tracking library, to detect the absolute pose of the object's links using a head-mounted camera; and a1 : changeAngle (2,1,90,180,1) a2 : changeAngle(1,0,180,90,2) a3 : changeAngle (3,2,90,180,3) a4 : changeAngle(1,0,270,180,4) Fig. 6.…”

Section: Validation Of the Frameworkmentioning

confidence: 99%

“…The ASP architecture used in this paper can be integrated with ROSo-Clingo [1], which is a system that combines the ASP solver Clingo (version 4) with the ROS middleware. In particular, it provides a high-level ASP-based interface to control the behaviour of a robot and to process the results of the execution of the actions.…”

Section: Related Workmentioning

confidence: 99%

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An ASP-Based Framework for the Manipulation of Articulated Objects Using Dual-Arm Robots

Bertolucci

Capitanelli

Dodaro

et al. 2019

Logic Programming and Nonmonotonic Reasoning

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The manipulation of articulated objects is of primary importance in robotics, and is one of the most complex robotics tasks. Traditionally, this problem has been tackled by developing ad-hoc approaches, that lack of flexibility and portability. In this paper we present a framework based on Answer Set Programming (ASP) for the automated manipulation of articulated objects in a robot architecture. In particular, ASP is employed for representing the configuration of the articulated object, for checking the consistency of the knowledge base, as well as for generating the sequence of manipulation actions. The framework is validated both in simulation and on the Baxter dual-arm manipulator, showing the applicability of the ASP methodology in this complex application scenario.

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“…With the launch of the idea that stable models (Gelfond and Lifschitz 1988) of a logic program can be used to encode search problems, a new programming paradigm, called Answer Set Programming (ASP) was born (Marek and Truszczyński 1999;Niemelä 1999;Lifschitz 1999). Nowadays, the fact that normal logic programs can effectively encode NP-complete decision and function problems is exploited in applications in many different domains such as robotics (Andres et al 2015), machine learning (Janhunen et al 2015;Bruynooghe et al 2015), phylogenetic inference (Koponen et al 2015;Brooks et al The support from the Finnish Center of Excellence in Computational Inference Research (COIN) funded by the Academy of Finland (under grant #251170) is gratefully acknowledged. 2007), product configuration (Tiihonen et al 2003), decision support for the Space Shuttle (Nogueira et al 2001), e-Tourism (Ricca et al 2010), and knowledge management (Grasso et al 2009).…”

Section: Introductionmentioning

confidence: 99%

Stable-unstable semantics: Beyond NP with normal logic programs

Bogaerts¹,

Janhunen²,

Tasharrofi³

2016

Theory and Practice of Logic Programming

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Standard answer set programming (ASP) targets at solving search problems from the first level of the polynomial time hierarchy (PH). Tackling search problems beyond NP using ASP is less straightforward. The class of disjunctive logic programs offers the most prominent way of reaching the second level of the PH, but encoding respective hard problems as disjunctive programs typically requires sophisticated techniques such as saturation or meta-interpretation. The application of such techniques easily leads to encodings that are inaccessible to non-experts. Furthermore, while disjunctive ASP solvers often rely on calls to a (co-)NP oracle, it may be difficult to detect from the input program where the oracle is being accessed. In other formalisms, such as Quantified Boolean Formulas (QBFs), the interface to the underlying oracle is more transparent as it is explicitly recorded in the quantifier prefix of a formula. On the other hand, ASP has advantages over QBFs from the modeling perspective. The rich high-level languages such as ASPCore-2 offer a wide variety of primitives that enable concise and natural encodings of search problems. In this paper, we present a novel logic programming-based modeling paradigm that combines the best features of ASP and QBFs. We develop so-called combined logic programs in which oracles are directly cast as (normal) logic programs themselves. Recursive incarnations of this construction enable logic programming on arbitrarily high levels of the PH. We develop a proof-of-concept implementation for our new paradigm. This paper is under consideration for acceptance in TPLP.

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Integrating ASP into ROS for Reasoning in Robots

Cited by 13 publications

References 12 publications

Multi-shot ASP solving with clingo

Multi-shot ASP solving with clingo

An ASP-Based Framework for the Manipulation of Articulated Objects Using Dual-Arm Robots

Stable-unstable semantics: Beyond NP with normal logic programs

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