Fernando Lobo Pereira

A maximum principle for optimal processes with discontinuous trajectories

A Maximum Principle is proved which governs solutions to dynamic optimization problems in which the controls driving the system may be impulsive and give rise to discontinuous trajectories. The approach, which involves approximating the problem by a conventional one and using Ekeland’s theorem, is new. It permits us to weaken very considerably the hypotheses under which Maximum Principles for such problems have previously been proved.

Necessary conditions of optimality for vector-valued impulsive control problems

Abstract A vector-valued impulsive control problem is considered whose dynamics, defined by a differential inclusion, are such that the vector fields associated with the singular term do not satisfy the so-called Frobenius condition. A concept of robust solution based on a new reparametrization procedure is adopted in order to derive necessary conditions of optimality. These conditions are obtained by taking a limit of those for an appropriate sequence of auxiliary “standard” optimal control problems approximating the original one. An example to illustrate the nature of the new optimality conditions is provided.

IMC: A communication protocol for networked vehicles and sensors

This paper presents the Inter-Module Communication (IMC) protocol, a message-oriented protocol designed and implemented in the Underwater Systems and Technology Laboratory (LSTS) to build interconnected systems of vehicles, sensors and human operators that are able to pursue common goals cooperatively by exchanging real-time information about the environment and updated objectives. IMC abstracts hardware and communication heterogeniety by providing a shared set of messages that can be serialized and transferred over different means.

A Nondegenerate Maximum Principle for the Impulse Control Problem with State Constraints

In this article, a free-time impulsive control problem with state constraints and equality and inequality constraints on the trajectory endpoints is considered. A weakened maximum principle is obtained for problems with data measurable in the time variable, being the time transversality conditions deduced with the help of some extra convexity assumption on the state constraints. In the case of smooth problems a nondegenerate maximum principle is derived by using a penalty function method.

Neptus - a framework to support multiple vehicle operation

This paper describes the development of a C3I (communications, command, control and intelligence/information) infrastructure, taking place at the Underwater Systems and Technology Laboratory (LSTS) of FEUP. This infrastructure, the Neptus framework, goal is to support the coordinated operation of heterogeneous teams, which include autonomous and remotely operated underwater, surface, land, and air vehicles and people. People perform a fundamental role, not only in the case of remotely operated vehicles, but also with autonomous vehicles where mix-initiative operation is a requirement. The operational scenarios for these teams are mainly environmental monitoring missions but could also include environmental disaster scenarios, rescue missions, etc. The Neptus distributed architecture is service oriented, which enables high degrees of interoperability between applications, of scalability (number of nodes), and of reconfiguration (number and type of nodes).

A versatile acoustic beacon for navigation and remote tracking of multiple underwater vehicles

In this paper, we present a low-cost versatile device developed to support the navigation of autonomous underwater vehicles. Unlike the usual transponders extensively used for long baseline acoustic navigation of a single vehicle, this device allows the navigation of multiple vehicles and the remote tracking of their positions, without any extra acoustic signals being transmitted. The navigation beacon has a radio buoy connected to an underwater reconfigurable multifrequency transponder. A remote tracking station receives data from the buoy and monitors the position of the vehicles in real time. We describe the mechanical, electronic and software modules involved, as well as the tracking algorithm, and we also present experimental data from an operational mission.

A new ROV design: issues on low drag and mechanical symmetry

This paper reports the design of a new remotely operated underwater vehicle (ROV), which has been developed at the Underwater Systems and Technology Laboratory (USTL) - University of Porto. This design is contextualized on the KOS project (Kits for underwater operations). The main issues addressed here concern directional drag minimization, symmetry, optimized thruster positioning, stability and layout of ROV components. This design is aimed at optimizing ROV performance for a set of different operational scenarios. This is achieved through modular configurations which are optimized for each different scenario.

Distribution rules with numeric attributes of interest

In this paper we introduce distribution rules, a kind of association rules with a distribution on the consequent. Distribution rules are related to quantitative association rules but can be seen as a more fundamental concept, useful for learning distributions. We formalize the main concepts and indicate applications to tasks such as frequent pattern discovery, sub group discovery and forecasting. An efficient algorithm for the generation of distribution rules is described. We also provide interest measures, visualization techniques and evaluation.

Stability for impulsive control systems

In this paper we extend the notion of the control Lyapounov pair of functions and derive a stability theory for impulsive control systems. The control system is a measure driven differential inclusion that is partly absolutely continuous and partly singular. Some examples illustrating the features of Lyapounov stability are provided.

SLAM algorithm applied to robotics assistance for navigation in unknown environments.

BackgroundThe combination of robotic tools with assistance technology determines a slightly explored area of applications and advantages for disability or elder people in their daily tasks. Autonomous motorized wheelchair navigation inside an environment, behaviour based control of orthopaedic arms or users preference learning from a friendly interface are some examples of this new field. In this paper, a Simultaneous Localization and Mapping (SLAM) algorithm is implemented to allow the environmental learning by a mobile robot while its navigation is governed by electromyographic signals. The entire system is part autonomous and part user-decision dependent (semi-autonomous). The environmental learning executed by the SLAM algorithm and the low level behaviour-based reactions of the mobile robot are robotic autonomous tasks, whereas the mobile robot navigation inside an environment is commanded by a Muscle-Computer Interface (MCI).MethodsIn this paper, a sequential Extended Kalman Filter (EKF) feature-based SLAM algorithm is implemented. The features correspond to lines and corners -concave and convex- of the environment. From the SLAM architecture, a global metric map of the environment is derived. The electromyographic signals that command the robots movements can be adapted to the patients disabilities. For mobile robot navigation purposes, five commands were obtained from the MCI: turn to the left, turn to the right, stop, start and exit. A kinematic controller to control the mobile robot was implemented. A low level behavior strategy was also implemented to avoid robots collisions with the environment and moving agents.ResultsThe entire system was tested in a population of seven volunteers: three elder, two below-elbow amputees and two young normally limbed patients. The experiments were performed within a closed low dynamic environment. Subjects took an average time of 35 minutes to navigate the environment and to learn how to use the MCI. The SLAM results have shown a consistent reconstruction of the environment. The obtained map was stored inside the Muscle-Computer Interface.ConclusionsThe integration of a highly demanding processing algorithm (SLAM) with a MCI and the communication between both in real time have shown to be consistent and successful. The metric map generated by the mobile robot would allow possible future autonomous navigation without direct control of the user, whose function could be relegated to choose robot destinations. Also, the mobile robot shares the same kinematic model of a motorized wheelchair. This advantage can be exploited for wheelchair autonomous navigation.