A proposal for a global task planning architecture using the RoboEarth cloud based framework

As robotic systems become more and more capable of assisting in human domains, methods are sought to compose robot executable plans from abstract human instructions. To cope with the semantically rich and highly expressive nature of human instructions, Hierarchical Task Network planning is often being employed along with domain knowledge to solve planning problems in a pragmatic way. Commonly, the domain knowledge is specific to the planning problem at hand, impeding re-use. Therefore this paper conceptualizes a global planning architecture, based on the worldwide accessible RoboEarth cloud framework. This architecture allows environmental state inference and plan monitoring on a global level. To enable plan re-use for future requests, the RoboEarth action language has been adapted to allow semantic matching of robot capabilities with previously composed plans

Design Considerations for a New Terminal Area Arrival Scheduler

Design of a terminal area arrival scheduler depends on the interrelationship between throughput, delay and controller intervention. The main contribution of this paper is an analysis of the above interdependence for several stochastic behaviors of expected system performance distributions in the aircraft s time of arrival at the meter fix and runway. Results of this analysis serve to guide the scheduler design choices for key control variables. Two types of variables are analyzed, separation buffers and terminal delay margins. The choice for these decision variables was tested using sensitivity analysis. Analysis suggests that it is best to set the separation buffer at the meter fix to its minimum and adjust the runway buffer to attain the desired system performance. Delay margin was found to have the least effect. These results help characterize the variables most influential in the scheduling operations of terminal area arrivals

Complexity Bounds for the Controllability of Temporal Networks with Conditions, Disjunctions, and Uncertainty

In temporal planning, many different temporal network formalisms are used to model real world situations. Each of these formalisms has different features which affect how easy it is to determine whether the underlying network of temporal constraints is consistent. While many of the simpler models have been well-studied from a computational complexity perspective, the algorithms developed for advanced models which combine features have very loose complexity bounds. In this paper, we provide tight completeness bounds for strong, weak, and dynamic controllability checking of temporal networks that have conditions, disjunctions, and temporal uncertainty. Our work exposes some of the subtle differences between these different structures and, remarkably, establishes a guarantee that all of these problems are computable in PSPACE

Uncertainty in Soft Temporal Constraint Problems:A General Framework and Controllability Algorithms forThe Fuzzy Case

In real-life temporal scenarios, uncertainty and preferences are often essential and coexisting aspects. We present a formalism where quantitative temporal constraints with both preferences and uncertainty can be defined. We show how three classical notions of controllability (that is, strong, weak, and dynamic), which have been developed for uncertain temporal problems, can be generalized to handle preferences as well. After defining this general framework, we focus on problems where preferences follow the fuzzy approach, and with properties that assure tractability. For such problems, we propose algorithms to check the presence of the controllability properties. In particular, we show that in such a setting dealing simultaneously with preferences and uncertainty does not increase the complexity of controllability testing. We also develop a dynamic execution algorithm, of polynomial complexity, that produces temporal plans under uncertainty that are optimal with respect to fuzzy preferences

Human Factors Implications of Continuous Descent Approach Procedures for Noise Abatement

Abstract Continuous Descent Approach (CDA) procedures can be effective at reducing aircraft noise in the vicinity of airports. The human factors implications for the air traffic controller of transitioning from conventional to CDA procedures are addressed in this paper. Different types of CDA procedures are introduced and models are developed of the controller tasks undertaken during current approach operations. The models are used to perform cognitive difference analyses to highlight the implications of using CDA procedures, particularly with respect to differences in intent, controllability and structure-based abstractions in the lateral, vertical and speed domains. An experiment is presented which probes the cognitive implications of changing speed profiles during the approach, which was one of the key differences between the procedures identified in the cognitive difference analysis. Based on the results, recommendations are made for CDA procedure design with a view to easing transition and controller acceptance

Managing temporal uncertainty under limited communication : a formal model of tight and loose team coordination

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2004.Includes bibliographical references (leaves 155-157).In the future, groups of autonomous robots will cooperate in large networks in order to achieve a common goal. These multi-agent systems will need to be able to execute cooperative temporal plans in the presence of temporal uncertainty and communication limitations. The duration of many planned activities will not be under direct control of the robots. In addition, robots will often not be able to communicate during plan execution. In order for the robots to robustly execute a cooperative plan, they will need to guarantee that a successful execution strategy exists, and provide a means to reactively compensate for the uncertainty in real-time. This thesis presents a multi-agent executive that enables groups of distributed autonomous robots to dynamically schedule temporally flexible plans that contain both temporal uncertainty under communication limitations. Previous work has presented controllability algorithms that compile the simple temporal networks with uncertainty, STNUs, into a form suitable for execution. This thesis extends the previous controllability algorithms to operate on two-layer plans that specify group level coordination at the highest level and agent level coordination at a lower level. We introduce a Hierarchical Reformulation (HR) algorithm that reformulates the two-layer plan in order to enable agents to dynamically adapt to uncertainty within each group plan and use a static execution strategy between groups in order to compensate for communication limitations. Formally, the HR algorithm ensures that the two-layer plan is strongly controllable at the highest level and dynamically controllable at the lower level. Furthermore, we introduce a new fast dynamic controllability algorithm that has been empirically shown to run in O(N³)(cont.) The Hierarchical Reformulation algorithm has been validated on a set of hand coded examples. The speed of the new fast dynamic controllability algorithm has been tested using a set of randomly generated problems.by John L. Stedl.S.M

Solving dynamic controllability problem of multi-agent plans with uncertainty using mixed integer linear programming.

Executing multi-agent missions requires managing the uncertainty about uncontrollable events. When communications are intermittent, it additionally requires for each agent to act only based on its local view of the problem, that is independently of events which are controlled or observed by the other agents. In this paper, we propose a new framework for dealing with such contexts, with a focus on mission plans involving temporal constraints. This framework, called Multi-agent Simple Temporal Network with Uncertainty (MaSTNU), is a combination between Multi-agent Simple Temporal Network (MaSTN) and Simple Temporal Network with Uncertainty (STNU).We define the dynamic controllability property for MaSTNU, and a method for computing offline valid execution strategies which are then dispatched between agents. This method is based on a mixed-integer linear programming formulation and can also be used to optimize criteria such as the temporal flexibility of multi-agent plans.

Investigating the Nature of and Methods for Managing Metroplex Operations

A combination of traffic demand growth, Next Generation Air Transportation System (NextGen) technologies and operational concepts, and increased utilization of regional airports is expected to increase the occurrence and severity of coupling between operations at proximate airports. These metroplex phenomena constrain the efficiency and/or capacity of airport operations and, in NextGen, have the potential to reduce safety and prevent environmental benefits. Without understanding the nature of metroplexes and developing solutions that provide efficient coordination of operations between closely-spaced airports, the use of NextGen technologies and distribution of demand to regional airports may provide little increase in the overall metroplex capacity. However, the characteristics and control of metroplex operations have not received significant study. This project advanced the state of knowledge about metroplexes by completing three objectives: 1. developed a foundational understand of the nature of metroplexes; 2. provided a framework for discussing metroplexes; 3. suggested and studied an approach for optimally managing metroplexes that is consistent with other NextGen concept

Synthèse de plans d’exécution multi-agents robustes aux incertitudes et à l’absence de communications

International audienceL’exécution de missions multi-agents nécessite de gérer les incertitudes induites par des événements incertains. Quand les communications sont intermittentes, il est nécessaire pour les agents d’agir selon leur vue locale du problème, de manière indépendante aux événements contrôlés ou observés par les autres agents. Dans ce papier, nous proposons un nouveau cadre de travail pour aborder cette problématique, en particulier pour les plans de missions impliquant des contraintes temporelles. Ce cadre de travail, appelé Réseau Temporel Simple Multi-agents avec incertitudes (MaSTNU), est une combinaison entre les cadres Réseau Temporel Simple Multi-agents (MaSTN) et Réseau Temporel Simple avec Incertitudes (STNU). Nous définissons la propriété de contrôlabilité dynamique pour les MaSTNU ainsi qu’une méthode pour calculer hors-ligne des stratégies d’exécution valides qui sont ensuite distribuées aux agents. Cette méthodeest basée sur une formulation en Programmation Linéaire en Nombres Entiers et peut également être utilisée pour optimiser certains critères telle que la flexibilité temporelle de plans d’exécution multi-agents

Autonomous Rendezvous with a non-cooperative satellite: trajectory planning and control

Con la nascita di nuove problematiche e nuove esigenze in ambito spaziale, le più importanti riguardanti il tema della mitigazione dei detriti spaziali o dell’assistenza e del servizio dei satelliti in orbita, lo scenario di rendez-vous autonomo tra un satellite inseguitore e un satellite target non cooperativo sta diventando sempre più centrale, ambizioso e accattivante. Il grande scoglio da superare, tuttavia, consiste nell’individuazione di una strategia di approccio robusta e vincente: mentre l’esecuzione di una manovra di rendez-vous e docking o cattura con satellite cooperativo è già stata collaudata e possiede una consolidata eredità di volo, il rendez-vous autonomo con satellite non cooperativo ed in stato di tombolamento è uno scenario agli albori, con pochi studi al riguardo. Lo scopo di questa tesi consiste nell’identificazione di una strategia di approccio che consideri le principali problematiche legate al tema in questione, ovvero la non-cooperazione e le scarse informazioni sullo stato di moto del target da raggiungere. Queste due complicazioni portano alla necessità di eseguire un moto di ispezione del satellite target e alla considerazione di numerosi vincoli nella progettazione della traiettoria di ispezione e di approccio. Un controllore adatto a trattare questo problema complesso e multi-vincolato è il Model Predictive Controller, in forma lineare o non lineare, abbinato ad un filtro di Kalman. La capacità di questo controllore di previsione e pianificazione di una traiettoria d’approccio, a partire da stime di posizione relativa tra target e inseguitore, permette di portare a termine la manovra in modo sicuro e robusto.According to the rise of new problems and new demands in the space field, the most important concerning the mitigation of space debris or the spacecraft on-orbit servicing and assistance themes, the Autonomous Rendezvous scenario between a chase satellite and a non-cooperative target satellite is becoming increasingly significant, ambitious, and attractive. The main issue to overcome, however, consists in the identification of a robust and successful approach strategy: while the execution of a rendezvous and docking or capture maneuver with a cooperative satellite has already been tested and holds a solid flight heritage, the autonomous rendezvous with a non-cooperative satellite in a state of tumbling motion is a scenario in the early days, with few studies about it and a not yet mature technology. The aim of this thesis consists in the identification of an approach strategy that deals with the main challenges related to the considered problem, namely non-cooperativeness and exiguous information about the target to be reached. These two issues lead to the need of performing an inspection motion and considering several constraints in the trajectory design. A controller suitable to handle this complex and multi-constrained problem is the Model Predictive Controller, in a linear or non-linear form, paired with a Kalman filter. The ability of this controller to predict and plan an approaching trajectory, starting from estimates of the relative position between the target and the chaser, allows to complete the approaching maneuver safely and in a robust way