75,566 research outputs found
Modelling Mixed Discrete-Continuous Domains for Planning
In this paper we present pddl+, a planning domain description language for
modelling mixed discrete-continuous planning domains. We describe the syntax
and modelling style of pddl+, showing that the language makes convenient the
modelling of complex time-dependent effects. We provide a formal semantics for
pddl+ by mapping planning instances into constructs of hybrid automata. Using
the syntax of HAs as our semantic model we construct a semantic mapping to
labelled transition systems to complete the formal interpretation of pddl+
planning instances. An advantage of building a mapping from pddl+ to HA theory
is that it forms a bridge between the Planning and Real Time Systems research
communities. One consequence is that we can expect to make use of some of the
theoretical properties of HAs. For example, for a restricted class of HAs the
Reachability problem (which is equivalent to Plan Existence) is decidable.
pddl+ provides an alternative to the continuous durative action model of
pddl2.1, adding a more flexible and robust model of time-dependent behaviour
CASP Solutions for Planning in Hybrid Domains
CASP is an extension of ASP that allows for numerical constraints to be added
in the rules. PDDL+ is an extension of the PDDL standard language of automated
planning for modeling mixed discrete-continuous dynamics.
In this paper, we present CASP solutions for dealing with PDDL+ problems,
i.e., encoding from PDDL+ to CASP, and extensions to the algorithm of the EZCSP
CASP solver in order to solve CASP programs arising from PDDL+ domains. An
experimental analysis, performed on well-known linear and non-linear variants
of PDDL+ domains, involving various configurations of the EZCSP solver, other
CASP solvers, and PDDL+ planners, shows the viability of our solution.Comment: Under consideration in Theory and Practice of Logic Programming
(TPLP
PDDL+ Planning with Hybrid Automata: Foundations of Translating Must Behavior
Planning in hybrid domains poses a special challenge due to the involved mixed discrete-continuous dynamics. A recent solving approach for such domains is based on applying model checking techniques on a translation of PDDL+ planning problems to hybrid automata. However, the proposed translation is limited because must behavior is only overapproximated, and hence, processes and events are not re- flected exactly. In this paper, we present the theoretical foundation of an exact PDDL+ translation. We propose a schema to convert a hybrid automaton with must transitions into an equivalent hybrid automaton featuring only may transitions
PDDL+ Planning with Hybrid Automata: Foundations of Translating Must Behavior
Planning in hybrid domains poses a special challenge due
to the involved mixed discrete-continuous dynamics. A recent
solving approach for such domains is based on applying
model checking techniques on a translation of PDDL+ planning
problems to hybrid automata. However, the proposed
translation is limited because must behavior is only overapproximated, and hence, processes and events are not reflected exactly. In this paper, we present the theoretical foundation of an exact PDDL+ translation. We propose a schema to convert a hybrid automaton with must transitions into an equivalent hybrid automaton featuring only may transitions
VAL : automatic plan validation, continuous effects and mixed initiative planning using PDDL
This paper describes aspects of our plan validation tool, VAL. The tool was initially developed to support the 3rd International Planning Competition, but has subsequently been extended in order to exploit its capabilities in plan validation and development. In particular, the tool has been extended to include advanced features of PDDL2.1 which have proved important in mixed-initiative planning in a space operations project. Amongst these features, treatment of continuous effects is the most significant, with important effects on the semantic interpretation of plans. The tool has also been extended to keep abreast of developments in PDDL, providing critical support to participants and organisers of the 4th IPC
Sampling-Based Methods for Factored Task and Motion Planning
This paper presents a general-purpose formulation of a large class of
discrete-time planning problems, with hybrid state and control-spaces, as
factored transition systems. Factoring allows state transitions to be described
as the intersection of several constraints each affecting a subset of the state
and control variables. Robotic manipulation problems with many movable objects
involve constraints that only affect several variables at a time and therefore
exhibit large amounts of factoring. We develop a theoretical framework for
solving factored transition systems with sampling-based algorithms. The
framework characterizes conditions on the submanifold in which solutions lie,
leading to a characterization of robust feasibility that incorporates
dimensionality-reducing constraints. It then connects those conditions to
corresponding conditional samplers that can be composed to produce values on
this submanifold. We present two domain-independent, probabilistically complete
planning algorithms that take, as input, a set of conditional samplers. We
demonstrate the empirical efficiency of these algorithms on a set of
challenging task and motion planning problems involving picking, placing, and
pushing
OCL Plus:Processes and Events in Object-Centred Planning
An important area in AI Planning is the expressiveness of planning domain
specification languages such as PDDL, and their aptitude for modelling real
applications. This paper presents OCLplus, an extension of a hierarchical object
centred planning domain definition language, intended to support the representation
of domains with continuous change. The main extension in OCLplus provides
the capability of interconnection between the planners and the changes that are
caused by other objects of the world. To this extent, the concept of event and process
are introduced in the Hierarchical Task Network (HTN), object centred planning
framework in which a process is responsible for either continuous or discrete
changes, and an event is triggered if its precondition is met. We evaluate the use of
OCLplus and compare it with a similar language, PDDL+
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