941 research outputs found

    Temporal Logic Motion Planning

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    In this paper, a critical review on temporal logic motion planning is presented. The review paper aims to address the following problems: (a) In a realistic situation, the motion planning problem is carried out in real-time, in a dynamic, uncertain and ever-changing environment, and (b) The accomplishment of high-level specification tasks which are more than just the traditional planning problem (i.e., start at initial state A and go to the goal state B) are considered. The use of theory of computation and formal methods, tools and techniques present a promising direction of research in solving motion planning problems that are influenced by high-level specification of complex tasks. The review, therefore, focuses only on those papers that use the aforementioned tools and techniques to solve a motion planning problem. A proposed robust platform that deals with the complexity of more expressive temporal logics is also presented.Defence Science Journal, 2010, 60(1), pp.23-38, DOI:http://dx.doi.org/10.14429/dsj.60.9

    Self-stabilizing robot formations over unreliable networks

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    We describe how a set of mobile robots can arrange themselves on any specified curve on the plane in the presence of dynamic changes both in the underlying ad hoc network and in the set of participating robots. Our strategy is for the mobile robots to implement a self-stabilizing virtual layer consisting of mobile client nodes, stationary Virtual Nodes (VNs), and local broadcast communication. The VNs are associated with predetermined regions in the plane and coordinate among themselves to distribute the client nodes relatively uniformly among the VNs' regions. Each VN directs its local client nodes to align themselves on the local portion of the target curve. The resulting motion coordination protocol is self-stabilizing, in that each robot can begin the execution in any arbitrary state and at any arbitrary location in the plane. In addition, self-stabilization ensures that the robots can adapt to changes in the desired target formation.National Science Foundation (U.S.) (Grant No. CNS-0614993

    From Verified Models to Verified Code for Safe Medical Devices

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    Medical devices play an essential role in the care of patients around the world, and can have a life-saving effect. An emerging category of autonomous medical devices like implantable pacemakers and implantable cardioverter defibrillators (ICD) diagnose conditions of the patient and autonomously deliver therapies. Without trained professionals in the loop, the software component of autonomous medical devices is responsible for making critical therapeutic decisions, which pose a new set of challenges to guarantee patient safety. As regulation effort to guarantee patient safety, device manufacturers are required to submit evidence for the safety and efficacy of the medical devices before they can be released to the market. Due to the closed-loop interaction between the device and the patient, the safety and efficacy of autonomous medical devices must ultimately be evaluated within their physiological context. Currently the primary closed-loop validation of medical devices is in form of clinical trials, in which the devices are evaluated on real patients. Clinical trials are expensive and expose the patients to risks associated with untested devices. Clinical trials are also conducted after device development, therefore issues found during clinical trials are expensive to fix. There is urgent need for closed-loop validation of autonomous medical devices before the devices are used in clinical trials. In this thesis, I used implantable cardiac devices to demonstrate the applications of model-based approaches during and after device development to provide confidence towards the safety and efficacy of the devices. A heart model structure is developed to mimic the electrical behaviors of the heart in various heart conditions. The heart models created with the model structure are capable of interacting with implantable cardiac devices in closed-loop and can provide physiological interpretations for a large variety of heart conditions. With the heart models, I demonstrated that closed-loop model checking is capable of identifying known and unknown safety violations within the pacemaker design. More importantly, I developed a framework to choose the most appropriate heart models to cover physiological conditions that the pacemaker may encounter, and provide physiological context to counter-examples returned by the model checker. A model translation tool UPP2SF is then developed to translate the pacemaker design in UPPAAL to Stateflow, and automatically generated to C code. The automated and rigorous translation ensures that the properties verified during model checking still hold in the implementation, which justifies the model checking effort. Finally, the devices are evaluated with a virtual patient cohort consists of a large number of heart models before evaluated in clinical trials. These in-silico pre-clinical trials provide useful insights which can be used to increase the success rate of a clinical trial. The work in this dissertation demonstrated the importance and challenges to represent physiological behaviors during closed-loop validation of autonomous medical devices, and demonstrated the capability of model-based approaches to provide safety and efficacy evidence during and after device development

    A graphical environment and applications for discrete event and hybrid systems in robotics and automation

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    technical reportIn this paper we present an overview for the development of a graphical environment for simulating, analyzing, synthesizing, monitoring, and controlling complex discrete event and hybrid systems within the robotics, automation, and intelligent system domain. We start by presenting an overview of discrete event and hybrid systems, and then discuss the proposed framework. We also present two applications within the robotics and automation domain for such complex systems. The first is for formulating an observer for manipulating agents, and the second is for designing sensing strategies for the inspection of machine parts

    RULES BASED MODELING OF DISCRETE EVENT SYSTEMS WITH FAULTS AND THEIR DIAGNOSIS

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    Failure diagnosis in large and complex systems is a critical task. In the realm of discrete event systems, Sampath et al. proposed a language based failure diagnosis approach. They introduced the diagnosability for discrete event systems and gave a method for testing the diagnosability by first constructing a diagnoser for the system. The complexity of this method of testing diagnosability is exponential in the number of states of the system and doubly exponential in the number of failure types. In this thesis, we give an algorithm for testing diagnosability that does not construct a diagnoser for the system, and its complexity is of 4th order in the number of states of the system and linear in the number of the failure types. In this dissertation we also study diagnosis of discrete event systems (DESs) modeled in the rule-based modeling formalism introduced in [12] to model failure-prone systems. The results have been represented in [43]. An attractive feature of rule-based model is it\u27s compactness (size is polynomial in number of signals). A motivation for the work presented is to develop failure diagnosis techniques that are able to exploit this compactness. In this regard, we develop symbolic techniques for testing diagnosability and computing a diagnoser. Diagnosability test is shown to be an instance of 1st order temporal logic model-checking. An on-line algorithm for diagnosersynthesis is obtained by using predicates and predicate transformers. We demonstrate our approach by applying it to modeling and diagnosis of a part of the assembly-line. When the system is found to be not diagnosable, we use sensor refinement and sensor augmentation to make the system diagnosable. In this dissertation, a controller is also extracted from the maximally permissive supervisor for the purpose of implementing the control by selecting, when possible, only one controllable event from among the ones allowed by the supervisor for the assembly line in automaton models
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