Automatic plan generation and adaptation by observation : supporting complex human planning

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

Sequential Single-Cluster Auctions for Multi-Robot Task Allocation

This thesis studies task allocation in multi-robot teams operating in dynamic environments. The multi-robot task allocation problem is a complex NP-Complete optimisation problem with globally optimal solutions often difficult to find. Because of this, the rapid generation of near optimal solutions to the problem that minimise task execution time and/or energy used by robots is highly desired. Our approach seeks to cluster together closely related tasks and then builds on existing distributed market-based auction architectures for distributing these sets of tasks among several autonomous robots. Dynamic environments introduce many challenges that are not found in closed systems. For instance, it is common for additional tasks to be inserted into a system after an initial solution to the task allocation problem is determined. Additionally, it is highly likely in long-term autonomous systems that individual robots may suffer some form of failure. The ability to alter plans to react to these types of challenges in a dynamic environment is required for the completion of all tasks. In our approach we allow the repeated formation and auctioning of task clusters with varying tasks. This allows us to react to and change the task allocation among robots during execution. Throughout this thesis we use empirical evaluation to study different approaches for forming clusters of tasks and the application of task clustering to distributed auctions for multi-robot task allocation problems. Our results show that allocating clusters of tasks to robots in solving these types of problems is a fast and effective method and produces near optimal solutions

A Framework for Developing Context-Aware Systems

In ubiquitous computing the environment constraints are often regarded as static and software applications are allowed to function in a mobile ecospace. However, in context-aware systems the environment attributes of software applications are dynamically changing. This dynamism of contexts must be accounted for in order to provide the true intended effect on the application of services. Consequently, context-aware software applications should perceive their context in a continuous manner and seamlessly adapt to it. This thesis investigates the process of constructing context-aware applications and identifies the main challenges in this domain. The two principal requirements are (1) formally defining what context is and expressing the enclosed semantics, (2) formally defining dynamic compositions of adaptations and triggering their responses to changes in the environment context. This thesis proposes a component-based architecture for a Context-aware Framework that would be used to bring awareness capabilities into applications. Two languages are formally designed. One is to formally express situations, leading to a context reasoner, and another is to formally express workflow, leading to timely triggering of reactions and enforcing policies. With these formalisms and a component design that can be formalized, the thesis work fulfills a formal approach to construct context-aware applications. A proof-ofconcept case study is implemented to examine the expressiveness of the framework design and test its implementation