Minimizing the number of actions in parallel planning

International audienceIn the domain of classical planning one distinguishes plans which are optimal in their number of actions, they are referred as sequential plans, from plans which are optimal in their number of levels, they are referred as parallel plans. Searching optimal sequential plans is generally considered harder than searching optimal parallel plans. Büttner and Rintanen have proposed a search procedure which computes plans whose numbers of levels are fixed and whose numbers of actions are minimal. This procedure is notably used to calculate optimal sequential plans, starting from an optimal parallel plan. In this paper we describe a similar approach, which we have developed from the planner FDP. The idea consists in maintaining two structures, the first one representing the parallel plan and the other representing the sequential plan, performing the choices simultaneously in both structures. The techniques which were developed in FDP to compute sequential plans or parallel plans enable failures detection in the two structures. Experimental results show that this approach is in some cases more efficient than FDP when searching optimal sequential plans

Taming Numbers and Durations in the Model Checking Integrated Planning System

The Model Checking Integrated Planning System (MIPS) is a temporal least commitment heuristic search planner based on a flexible object-oriented workbench architecture. Its design clearly separates explicit and symbolic directed exploration algorithms from the set of on-line and off-line computed estimates and associated data structures. MIPS has shown distinguished performance in the last two international planning competitions. In the last event the description language was extended from pure propositional planning to include numerical state variables, action durations, and plan quality objective functions. Plans were no longer sequences of actions but time-stamped schedules. As a participant of the fully automated track of the competition, MIPS has proven to be a general system; in each track and every benchmark domain it efficiently computed plans of remarkable quality. This article introduces and analyzes the most important algorithmic novelties that were necessary to tackle the new layers of expressiveness in the benchmark problems and to achieve a high level of performance. The extensions include critical path analysis of sequentially generated plans to generate corresponding optimal parallel plans. The linear time algorithm to compute the parallel plan bypasses known NP hardness results for partial ordering by scheduling plans with respect to the set of actions and the imposed precedence relations. The efficiency of this algorithm also allows us to improve the exploration guidance: for each encountered planning state the corresponding approximate sequential plan is scheduled. One major strength of MIPS is its static analysis phase that grounds and simplifies parameterized predicates, functions and operators, that infers knowledge to minimize the state description length, and that detects domain object symmetries. The latter aspect is analyzed in detail. MIPS has been developed to serve as a complete and optimal state space planner, with admissible estimates, exploration engines and branching cuts. In the competition version, however, certain performance compromises had to be made, including floating point arithmetic, weighted heuristic search exploration according to an inadmissible estimate and parameterized optimization

Answer Set Planning Under Action Costs

Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language Kc, which extends the declarative planning language K by action costs. Kc provides the notion of admissible and optimal plans, which are plans whose overall action costs are within a given limit resp. minimum over all plans (i.e., cheapest plans). As we demonstrate, this novel language allows for expressing some nontrivial planning tasks in a declarative way. Furthermore, it can be utilized for representing planning problems under other optimality criteria, such as computing ``shortest'' plans (with the least number of steps), and refinement combinations of cheapest and fastest plans. We study complexity aspects of the language Kc and provide a transformation to logic programs, such that planning problems are solved via answer set programming. Furthermore, we report experimental results on selected problems. Our experience is encouraging that answer set planning may be a valuable approach to expressive planning systems in which intricate planning problems can be naturally specified and solved

Proposals for Flashflood Management in Western Argentina: Case Study: The Metropolitan Area of Greater Mendoza

Las cuencas hidrográficas situadas en el oeste del Gran Mendoza (Argentina) son ejemplos típicos de las zonas directa o indirectamente afectadas por inundaciones repentinas. Gran Mendoza está invadiendo zonas con un relieve pronunciado (vertiente oriental de la Precordillera, el piedemonte y otras unidades menores) con fuertes presiones humanas en un entorno frágil. Hoy en día, la parte occidental del Gran Mendoza se cubre con superficies pavimentadas y edificios, poniendo en peligro la ciudad situada aguas abajo. Con el fin de mitigar los efectos negativos del uso y ocupación del piedemonte, un conjunto de medidas estructurales y no estructurales y un modelo de planificación urbana, con nuevas propuestas de desarrollo y arquitectura urbana, se han ideado. Estas medidas implican el control de inundaciones, control de la erosión, la repoblación forestal, la gestión del hábitat, control de las prácticas de extracción (agregados, fauna, vegetación, etc.) y la educación. El nuevo modelo de planificación urbana se basa en la preservación del carácter natural de la tierra y el manejo adecuado de los excedentes de agua (detección de escorrentía en el área de origen, la retención de sistema de drenaje, lo que aumenta la capacidad de drenaje y reducir al mínimo los impactos en entornos de aguas abajo, y la creación de áreas para amortiguar el escurrimiento). Muchas de estas medidas se han desarrollado y demostrado éxito a nivel local.Fil: Vich, Alberto Ismael Juan. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentina. Universidad Nacional de Cuyo. Facultad de Filosofía y Letras. Instituto de Estudios del Ambiente y los Recursos Naturales; ArgentinaFil: López Rodríguez, Mariela Beatriz. Universidad Nacional de Cuyo. Facultad de Filosofía y Letras. Instituto Cartografía, Investigación y Formación para el Ordenamiento Territorial; ArgentinaFil: Lauro, Carolina. Universidad Nacional de Cuyo. Facultad de Filosofía y Letras. Instituto de Estudios del Ambiente y los Recursos Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; ArgentinaFil: Vaccarino Pasquali, Emilce Liliana Belén. Universidad Nacional de Cuyo. Facultad de Filosofía y Letras. Instituto de Estudios del Ambiente y los Recursos Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentin

Bi-objective modeling approach for repairing multiple feature infrastructure systems

A bi-objective decision aid model for planning long-term maintenance of infrastructure systems is presented, oriented to interventions on their constituent elements, with two upgrade levels possible for each element (partial/full repairs). The model aims at maximizing benefits and minimizing costs, and its novelty is taking into consideration, and combining, the system/element structure, volume discounts, and socioeconomic factors. The model is tested with field data from 229 sidewalks (systems) and compared to two simpler repair policies, of allowing only partial or full repairs. Results show that the efficiency gains are greater in the lower mid-range budget region. The proposed modeling approach is an innovative tool to optimize cost/benefits for the various repair options and analyze the respective trade-offs.info:eu-repo/semantics/publishedVersio

Learning to Prevent Monocular SLAM Failure using Reinforcement Learning

Monocular SLAM refers to using a single camera to estimate robot ego motion while building a map of the environment. While Monocular SLAM is a well studied problem, automating Monocular SLAM by integrating it with trajectory planning frameworks is particularly challenging. This paper presents a novel formulation based on Reinforcement Learning (RL) that generates fail safe trajectories wherein the SLAM generated outputs do not deviate largely from their true values. Quintessentially, the RL framework successfully learns the otherwise complex relation between perceptual inputs and motor actions and uses this knowledge to generate trajectories that do not cause failure of SLAM. We show systematically in simulations how the quality of the SLAM dramatically improves when trajectories are computed using RL. Our method scales effectively across Monocular SLAM frameworks in both simulation and in real world experiments with a mobile robot.Comment: Accepted at the 11th Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP) 2018 More info can be found at the project page at https://robotics.iiit.ac.in/people/vignesh.prasad/SLAMSafePlanner.html and the supplementary video can be found at https://www.youtube.com/watch?v=420QmM_Z8v