Autonomous vehicles are increasingly being used in mission-critical applications, and robust methods are needed for controlling these inherently unreliable and complex systems. This thesis advocates the use of model-based programming, which allows mission designers to program autonomous missions at the level of a coach or wing commander. To support such a system, this thesis presents the Spock generative planner. To generate plans, Spock must be able to piece together vehicle commands and team tactics that have a complex behavior represented by concurrent processes. This is in contrast to traditional planners, whose operators represent simple atomic or durative actions. Spock represents operators using the RMPL language, which describes behaviors using parallel and sequential compositions of state and activity episodes. RMPL is useful for controlling mobile autonomous missions because it allows mission designers to quickly encode expressive activity models using object-oriented design methods and an intuitive set of activity combinators. Spock also is significant in that it uniformly represents operators and plan-space processes in terms of Temporal Plan Networks, which support temporal flexibility for robust plan execution. Finally, Spock is implemented as a forward progression optimal planner that walks monotonically forward through plan processes, closing any open conditions and resolving any conflicts. This thesis describes the Spock algorithm in detail, along with example problems and test results.

Autonomous vehicles are increasingly being used in mission-critical applications, and robust methods are needed for controlling these inherently unreliable and complex systems. This thesis advocates the use of model-based programming, which allows mission designers to program autonomous missions at the level of a coach or wing commander. To support such a system, this thesis presents the Spock generative planner. To generate plans, Spock must be able to piece together vehicle commands and team tactics that have a complex behavior represented by concurrent processes. This is in contrast to traditional planners, whose operators represent simple atomic or durative actions. Spock represents operators using the RMPL language, which describes behaviors using parallel and sequential compositions of state and activity episodes. RMPL is useful for controlling mobile autonomous missions because it allows mission designers to quickly encode expressive activity models using object-oriented design methods and an intuitive set of activity combinators. Spock also is significant in that it uniformly represents operators and plan-space processes in terms of Temporal Plan Networks, which support temporal flexibility for robust plan execution. Finally, Spock is implemented as a forward progression optimal planner that walks monotonically forward through plan processes, closing any open conditions and resolving any conflicts. This thesis describes the Spock algorithm in detail, along with example problems and test results.

In order for a mobile robot to complete its task it must be able to plan and follow a trajectory. Depending on the environment, it may also be necessary to follow a given velocity profile. This is known as temporal planning. Temporal planning can be used to minimize time of motion and to avoid moving obstacles. For example, assuming the mobile robot is an intelligent wheelchair, it must follow a prescribed path (sidewalk, hospital corridor) while following a strict speed limit (slowing down for pedestrians, cars). Computing a realistic velocity profile for a mobile robot is a challenging task due to a large number of kinematic and dynamic constraints that are involved. Unlike prior works which performed temporal planning in a 2-dimensional environment, this thesis presents a new temporal planning algorithm in a 3-dimensional environment. This algorithm is implemented on a wheeled mobile robot that is to be used in a healthcare setting. The path planning stage is accomplished by using cubic spline functions. A rudimentary trajectory is created by assigning an arbitrary time to each segment of the path. This trajectory is made feasible by applying a number of constraints and using a linear scaling technique. When a velocity profile is provided, a non-linear time scaling technique is used to fit the robots center linear velocity to the specified velocity. A method for avoiding moving obstacles is also implemented. Both simulation and experimental results for the wheeled mobile robot are presented. These results show good agreement with each other. For both simulation and experimentation, six different examples of paths in the Engineering Building of the University of Saskatchewan, were used. Experiments were performed using the PowerBot mobile robot in the robotics lab at the University of Saskatchewan.

In order for a mobile robot to complete its task it must be able to plan and follow a trajectory. Depending on the environment, it may also be necessary to follow a given velocity profile. This is known as temporal planning. Temporal planning can be used to minimize time of motion and to avoid moving obstacles. For example, assuming the mobile robot is an intelligent wheelchair, it must follow a prescribed path (sidewalk, hospital corridor) while following a strict speed limit (slowing down for pedestrians, cars). Computing a realistic velocity profile for a mobile robot is a challenging task due to a large number of kinematic and dynamic constraints that are involved. Unlike prior works which performed temporal planning in a 2-dimensional environment, this thesis presents a new temporal planning algorithm in a 3-dimensional environment. This algorithm is implemented on a wheeled mobile robot that is to be used in a healthcare setting. The path planning stage is accomplished by using cubic spline functions. A rudimentary trajectory is created by assigning an arbitrary time to each segment of the path. This trajectory is made feasible by applying a number of constraints and using a linear scaling technique. When a velocity profile is provided, a non-linear time scaling technique is used to fit the robots center linear velocity to the specified velocity. A method for avoiding moving obstacles is also implemented. Both simulation and experimental results for the wheeled mobile robot are presented. These results show good agreement with each other. For both simulation and experimentation, six different examples of paths in the Engineering Building of the University of Saskatchewan, were used. Experiments were performed using the PowerBot mobile robot in the robotics lab at the University of Saskatchewan.

abstract: In this dissertation I develop a deep theory of temporal planning well-suited to analyzing, understanding, and improving the state of the art implementations (as of 2012). At face-value the work is strictly theoretical; nonetheless its impact is entirely real and practical. The easiest portion of that impact to highlight concerns the notable improvements to the format of the temporal fragment of the International Planning Competitions (IPCs). Particularly: the theory I expound upon here is the primary cause of--and justification for--the altered (i) selection of benchmark problems, and (ii) notion of "winning temporal planner". For higher level motivation: robotics, web service composition, industrial manufacturing, business process management, cybersecurity, space exploration, deep ocean exploration, and logistics all benefit from applying domain-independent automated planning technique. Naturally, actually carrying out such case studies has much to offer. For example, we may extract the lesson that reasoning carefully about deadlines is rather crucial to planning in practice. More generally, effectively automating specifically temporal planning is well-motivated from applications. Entirely abstractly, the aim is to improve the theory of automated temporal planning by distilling from its practice. My thesis is that the key feature of computational interest is concurrency. To support, I demonstrate by way of compilation methods, worst-case counting arguments, and analysis of algorithmic properties such as completeness that the more immediately pressing computational obstacles (facing would-be temporal generalizations of classical planning systems) can be dealt with in theoretically efficient manner. So more accurately the technical contribution here is to demonstrate: The computationally significant obstacle to automated temporal planning that remains is just concurrency. / Dissertation/Thesis / Ph.D. Computer Science 2012

The problem of domain-independent automated planning has been a topic of research in Artificial Intelligence since the very beginnings of the field. Due to the desire not to rely on vast quantities of problem specific knowledge, the most widely adopted approach to automated planning is search. The topic of this thesis is the development of methods for achieving effective search control for domain-independent optimal planning through the construction of admissible heuristics. The particular planning problem considered is the so called “classical” AI planning problem, which makes several restricting assumptions. Optimality with respect to two measures of plan cost are considered: in planning with additive cost, the cost of a plan is the sum of the costs of the actions that make up the plan, which are assumed independent, while in planning with time, the cost of a plan is the total execution time – makespan – of the plan. The makespan optimization objective can not, in general, be formulated as a sum of independent action costs and therefore necessitates a problem model slightly different from the classical one. A further small extension to the classical model is made with the introduction of two forms of capacitated resources. Heuristics are developed mainly for regression planning, but based on principles general enough that heuristics for other planning search spaces can be derived on the same basis. The thesis describes a collection of methods, including the hm, additive hm and improved pattern database heuristics, and the relaxed search and boosting techniques for improving heuristics through limited search, and presents two extended experimental analyses of the developed methods, one comparing heuristics for planning with additive cost and the other concerning the relaxed search technique in the context of planning with time, aimed at discovering the characteristics of problem domains that determine the relative effectiveness of the compared methods. Results indicate that some plausible such characteristics have been found, but are not entirely conclusive.

Neste trabalho se estuda os principais métodos de planejamento temporal. Propõe soluções baseadas no grafo de planos, bem como soluções baseadas na tradução deste em Redes de Petri Temporais. Objetivando a contextualização do cenário em que o presente trabalho se insere, é apresentada uma revisão dos algoritmos que fazem o tratamento de problemas de planejamento clássico e o planejamento temporal. Propõe-se um novo método de tratamento temporal sobre o grafo de planos e sua tradução para uma Rede de Petri Temporal. / In this work it is studied the main methods of temporal planning. It is proposed solutions based on graph of plans as well as solutions based on the translation of graph of plans into time Petri nets. A review is presented about the algorithms for the treatment of classical planning and temporal planning. This review aims at to present the context of this work. Subsequently, it is proposed a new method of temporal treatment for the graph of plans and its translation into a time Petri net.

Neste trabalho se estuda os principais métodos de planejamento temporal. Propõe soluções baseadas no grafo de planos, bem como soluções baseadas na tradução deste em Redes de Petri Temporais. Objetivando a contextualização do cenário em que o presente trabalho se insere, é apresentada uma revisão dos algoritmos que fazem o tratamento de problemas de planejamento clássico e o planejamento temporal. Propõe-se um novo método de tratamento temporal sobre o grafo de planos e sua tradução para uma Rede de Petri Temporal. / In this work it is studied the main methods of temporal planning. It is proposed solutions based on graph of plans as well as solutions based on the translation of graph of plans into time Petri nets. A review is presented about the algorithms for the treatment of classical planning and temporal planning. This review aims at to present the context of this work. Subsequently, it is proposed a new method of temporal treatment for the graph of plans and its translation into a time Petri net.

在瞬息萬變的工作環境中，資訊量龐大而繁雜，工作團體成員自身的時間分配，影響著任務執行期間的團體運作。現代快速而多工的工作要求，團體成員的多工作業特徵顯得更為重要。有鑑於此，本研究以此為主題，同時探究多工作業多元性對團體表現與團體成員壓力之影響。而過去團體多元性研究即指出，多元性可能會同時具有正、反面影響，本研究嘗試探討多工作業多元性所形成之優劣，並進一步檢驗團體的時間規劃所可能扮演的跨層次調節角色，以知在甚麼情況下多工作業多元性能具有最大的效益。採用問卷法施測，蒐集了50份有效之團體成套問卷，包含192名全職工作者。結果發現，多工作業多元性有助於團體任務績效之表現，並在額外分析中發現了任務相依性的三階調節效果。在個體層次中，個體與團體之時間特徵差異會直接導致個體壓力與退縮反應，其中在高時間規劃情況下，此差異與個體壓力之關係會削弱。最後依據研究結果進行討論，並說明理論貢獻、實務意涵以及未來研究方向。 / Temporal individual differences are an under-explored, but research-worthy form of diversity in groups. This study examines how group temporal diversity–variation in members' polychronicity—can be effectively managed to maximize group performance. Besides, how this difference effect individual stress is also examined. Results from 50 work groups reveal that polychronicity diversity had a positive influence on task-oriented group performance. Additional analysis found that task interdependence moderated the interaction effect of temporal planning and polychronicity diversity on task-oriented group performance. In other hand, when individual and work group polychronicity were more incongruent, individual stress and withdrawal behavior increased. And the influence of the incongrunce on individual stress was less positive under conditions of stronger group temporal planning than under weaker group temporal planning. Results can be used to effectively compose groups in organizations and guide future group composition research.

La planification temporelle constitue conceptuellement une partie du raisonnement temporelle et il appartient au domaine de recherche de l'intelligence artificielle. La planification temporelle peut être considérée comme une extension de la planification classique par les aspects temporels de l'action. La planification temporelle est généralement complété par des préférences ou des types différents decontraintes imposées à l'exécution des actiones. Il existe de nombreuses approches à ce problème. D'une part, il existe différents paradigmes pour la planification temporelle, par example: la planification par un recherche d'une solution optimale dans des graphes de planification (STRIPS), la planification via la satisfiabilité ou la planification pardes processus de Markov. Ces approches sont mutuellement incompatibles. D'autre part, la planification temporelle exige une sujet-spécification – comme il est défini d'une manière méthodologique. Selon cette situation, cette thèse vise à proposer une analyse approfondi de la planification avec des contraintes floues qui contient quelques remèdes à ces difficultés. À savoir, deux approches à la représentation et la modélisation de ces questions sont mises.Dans la première (chapitre 2, chapitre 3) - les relations floues d'Allen en tant que contraintes temporelles floues sont représentés par des normes de convolutions dans un espace de Banach des fonctions intégrables de Lebesgue. Cela nous permet de nous immergerles relations d'Allen dans les contextes computationnels de la planification temporelle (basée sur STRIPS et sur la procedure de Davis-Putnam) et d'élucider leur nature quantitative. Cette approche est développée dans un contexte des problèmes par systèmes multi-agents comme un sujet de cette approche. Dans les chapitres 4 et 5 les contraintes temporelles floues avec flou – introduit par préférences - sont représentées en termes logiques de la logique préférentielle de Halpern-Shoham. Cela nous permet d'adopter ces resultats dans une construction du contrôleur du plan. Cette approche est développée dans un contexte du problème du voyageur de commerce. Enfin, une tentative de réconcilier ces deux lignes de représentation des contraintes temporelles floues a été proposée dans le dernier chapitre. / Temporal planning forms conceptually a part of temporal reasoning and it belongs to research area of Artificial Intelligence and it may be seen as an extension of classical planning by temporal aspects of acting. Temporal planing is usually complemented by considering preferences or different types of temporal constraints imposed on execution of actions. There exist many approaches to this issue. One one hand, there are different paradigms to temporal planning, such as: planning via search in graphs (STRIPS), planning via satisfiability or planning in terms of Markov processes. These approaches are mutually incompatible. In addition, temporal planning requires a subject-specification as it is rather defined in a methodological way. On the other hand, temporal constraints are represented and modeled in different ways dependently on their quantitative or qualitative nature. In particular, Allen’s relations between temporal intervals – an important class of temporal constraints – do not have any quantitative aspects and cannot be considered in computational contexts. According to this situation, this PhD-thesis is aimed at the proposing a depth-analysis of temporal planning with fuzzy constraints which contains some remedies on these difficulties. Namely, two approaches to the representation and modeling of these issues are put forward. In the first one (chapter 2, chapter 3) – fuzzy Allen’s relations as fuzzy temporal constraints are represented by norms of convolutions in a Banach space of Lebesgue integrable functions. It allows us immerse Allen’s relations in the computational contexts of temporal planning (based on STRIPS and on DavisPutnam procedure) and to elucidate their quantitative nature. This approach is developed in a context of Multi-Agent Problem as a subject basis of this approach. In the second one (chapter 4, chapter 5) – fuzzy temporal constrains with fuzziness introduced by preferences are represented in a logical terms of Preferential Halpern-Shoham Logic. It allows us to adopt these result in a construction of the plan controller. This approach is developed in a context of Temporal Traveling Salesman Problem as a subject basis of this approach. Finally, an attempt to reconcile these two lines of representation of fuzzy temporal constraints was also proposed.