Plan Projection, Execution, and Learning for Mobile Robot Control

Most state-of-the-art hybrid control systems for mobile robots are decomposed into different layers. While the deliberation layer reasons about the actions required for the robot in order to achieve a given goal, the behavioral layer is designed to enable the robot to quickly react to unforeseen events. This decomposition guarantees a safe operation even in the presence of unforeseen and dynamic obstacles and enables the robot to cope with situations it was not explicitly programmed for. The layered design, however, also leaves us with the problem of plan execution. The problem of plan execution is the problem of arbitrating between the deliberation- and the behavioral layer. Abstract symbolic actions have to be translated into streams of local control commands. Simultaneously, execution failures have to be handled on an appropriate level of abstraction. It is now widely accepted that plan execution should form a third layer of a hybrid robot control system. The resulting layered architectures are called three-tiered architectures, or 3T architectures for short. Although many high level programming frameworks have been proposed to support the implementation of the intermediate layer, there is no generally accepted algorithmic basis for plan execution in three-tiered architectures. In this thesis, we propose to base plan execution on plan projection and learning and present a general framework for the self-supervised improvement of plan execution. This framework has been implemented in APPEAL, an Architecture for Plan Projection, Execution And Learning, which extends the well known RHINO control system by introducing an execution layer. This thesis contributes to the field of plan-based mobile robot control which investigates the interrelation between planning, reasoning, and learning techniques based on an explicit representation of the robot's intended course of action, a plan. In McDermott's terminology, a plan is that part of a robot control program, which the robot cannot only execute, but also reason about and manipulate. According to that broad view, a plan may serve many purposes in a robot control system like reasoning about future behavior, the revision of intended activities, or learning. In this thesis, plan-based control is applied to the self-supervised improvement of mobile robot plan execution

Definition and verification of a set of reusable reference architectures for hybrid vehicle development

Current concerns regarding climate change and energy security have resulted in an increasing demand for low carbon vehicles, including: more efficient internal combustion engine vehicles, alternative fuel vehicles, electric vehicles and hybrid vehicles. Unlike traditional internal combustion engine vehicles and electric vehicles, hybrid vehicles contain a minimum of two energy storage systems. These are required to deliver power through a complex powertrain which must combine these power flows electrically or mechanically (or both), before torque can be delivered to the wheel. Three distinct types of hybrid vehicles exist, series hybrids, parallel hybrids and compound hybrids. Each type of hybrid presents a unique engineering challenge. Also, within each hybrid type there exists a wide range of configurations of components, in size and type. The emergence of this new family of hybrid vehicles has necessitated a new component to vehicle development, the Vehicle Supervisory Controller (VSC). The VSC must determine and deliver driver torque demand, dividing the delivery of that demand from the multiple energy storage systems as a function of efficiencies and capacities. This control component is not commonly a standalone entity in traditional internal combustion vehicles and therefore presents an opportunity to apply a systems engineering approach to hybrid vehicle systems and VSC control system development. A key non-­‐functional requirement in systems engineering is reusability. A common method for maximising system reusability is a Reference Architecture (RA). This is an abstraction of the minimum set of shared system features (structure, functions, interactions and behaviour) that can be applied to a number of similar but distinct system deployments. It is argued that the employment of RAs in hybrid vehicle development would reduce VSC development time and cost. This Thesis expands this research to determine if one RA is extendable to all hybrid vehicle types and combines the scientific method with the scenario testing method to verify the reusability of RAs by demonstration. A set of hypotheses are posed: Can one RA represent all hybrid types? If not, can a minimum number of RAs be defined which represents all hybrid types? These hypotheses are tested by a set of scenarios. The RA is used as a template for a vehicle deployment (a scenario), which is then tested numerically, thereby verifying that the RA is valid for this type of vehicle. This Thesis determines that two RAs are required to represent the three hybrid vehicle types. One RA is needed for series hybrids, and the second RA covers parallel and compound hybrids. This is done at a level of abstraction which is high enough to avoid system specific features but low enough to incorporate detailed control functionality. One series hybrid is deployed using the series RA into simulation, hardware and onto a vehicle for testing. This verifies that the series RA is valid for this type of vehicle. The parallel RA is used to develop two sub-­‐types of parallel hybrids and one compound hybrid. This research has been conducted with industrial partners who value, and are employing, the findings of this research in their hybrid vehicle development programs

Supervisory control of fuzzy discrete event systems with applications to mobile robotics

Fuzzy Discrete Event Systems (FDES) were proposed in the literature for modeling and control of a class of event driven and asynchronous dynamical systems that are affected by deterministic uncertainties and vagueness on their representations. In contrast to classical crisp Discrete Event Systems (DES), which have been explored to a sufficient extent in the past, an in-depth study of FDES is yet to be performed, and their feasible real-time application areas need to be further identified. This research work intends to address the supervisory control problem of FDES broadly, while formulating new knowledge in the area. Moreover, it examines the possible applications of these developments in the behavior-based mobile robotics domain. An FDES-based supervisory control framework to facilitate the behavior-based control of a mobile robot is developed at first. The proposed approach is modular in nature and supports behavior integration without making state explosion. Then, this architecture is implemented in simulation as well as in real-time on a mobile robot moving in unstructured environments, and the feasibility of the approach is validated. A general decentralized supervisory control theory of FDES is then established for better information association and ambiguity management in large-scale and distributed systems, while providing less complexity of control computation. Furthermore, using the proposed architecture, simulation and real-time experiments of a tightly-coupled multi-robot object manipulation task are performed. The results are compared with centralized FDES-based and decentralized DES-based approaches. -- A decentralized modular supervisory control theory of FDES is then established for complex systems having a number of modules that are concurrently operating and also containing multiple interactions. -- Finally, a hierarchical supervisory control theory of FDES is established to resolve the control complexity of a large-scale compound system by modularizing the system vertically and assigning multi-level supervisor hierarchies. As a proof-of-concept example to the established theory, a mobile robot navigation problem is discussed. This research work will contribute to the literature by developing novel knowledge and related theories in the areas of decentralized, modular and hierarchical supervisory control of FDES. It also investigates the applicability of these contributions in the mobile robotics arena