35062719
Vision Guided Circumnavigating Autonomous Robots
We present a system for vision guided autonomous circumnavigation, allowing a mobile robot to navigate safely around objects of arbitrary pose, and avoid obstacles. The system performs model-based object recognition from an intensity image. By enabling robots to recognize and navigate with respect to particular objects, this system empowers robots to perform deterministic actions on specific objects, rather than general exploration and navigation as emphasized in much of the current literature. This paper describes a fully integrated system, and, in particular, introduces canonical-views. Further, we derive a direct algebraic method for finding object pose and position for the four-dimensional case of a ground-based robot with uncalibrated vertical movement of its camera. Vision for mobile robots can be treated as a very different problem to traditional computer vision, as mobile robots have a characteristic perspective, and there is a causal relation between robot actions and view changes. Canonical-views are a novel, active object representation designed specifically to take advantage of the constraints of the robot navigation problem to allow efficient recognition and navigation.
207320245
Hidden Markov models with factored Gaussian mixtures densities
We present a factorial representation of Gaussian mixture models for observation densities in hidden Markov models (HMMs), which uses the factorial learning in the HMM framework. We derive the reestimation formulas for estimating the factorized parameters by the Expectation Maximization (EM) algorithm and propose a novel method for initializing them. To compare the performances of the proposed models with that of the factorial hidden Markov models and HMMs, we have carried out extensive experiments which show that this modelling approach is effective and robust.
2364735
Embodied categorisation for vision-guided mobile robots
This paper outlines a philosophical and psycho-physiological basis for embodied perception, and develops a framework for conceptual embodiment of vision-guided robots. We argue that categorisation is important in all stages of robot vision. Further, that classical computer vision is unsuitable for this categorisation, however, through conceptual embodiment, active perception can be effective. We present a methodology for developing vision-guided robots that applies embodiment, explicitly and implicitly, in categorising visual data to facilitate efficient perception and action. Finally, we present systems developed using this methodology, and demonstrate that embodied categorisation can make algorithms more efficient and robust.
10848842
Vision Guided Circumnavigating Autonomous Robots
In this paper, we propose a system for vision guided autonomous circumnavigation, allowing robots to navigate around objects of arbitrary pose. The system performs knowledge-based object recognition from an intensity image using a canonical viewer-centred model. A path planned from a geometric model then guides the robot in circum-navigating the object. This system can be used in many applications where robots have to recognize and manipulate objects of unknown pose and placement. Such applications occur in a variety of contexts such as factory automation, underwater and space exploration, and nuclear power station maintenance. We also define a canonical-view graph to model objects, which is a viewer-centred representation.
7502395
Dynamic image sequence analysis using fuzzy measures
In this paper, we present an image understanding system using fuzzy sets and fuzzy measures. This system is based on a symbolic object-oriented image interpretation system. We apply a simple, powerful three-dimensional (3-D) recursive filter to tracking moving objects in a dynamic image sequence. This filter has a time-varying 3-D frequency-planar passband that is adapted in a feedback system to automatically track moving objects. However, as objects in the image sequence are not well-defined and are engaged in dynamic activities, their shapes and trajectories in most cases can be described only vaguely. In order to handle these uncertainties, we use fuzzy measures to capture subtle variations and manage the uncertainties involved. This enables us to develop an image understanding system that produces a very natural output. We demonstrate the effectiveness of our system with complex real traffic scenes.
14780024
Fuzzy causal networks: general model, inference, and convergence
In this paper, we first propose a general framework for fuzzy causal networks (FCNs). Then, we study the dynamics and convergence of such general FCNs. We prove that any general FCN with constant weight matrix converges to a limit cycle or a static state, or the trajectory of the FCN is not repetitive. We also prove that under certain conditions a discrete state general FCN converges to its limit cycle or static state in O(n) steps, where n is the number of vertices of the FCN. This is in striking contrast with the exponential running time 2/sup n/, which is accepted widely for classic FCNs.
7545798
Verification of fault tolerance and real time
A transformational method is given for specifying and verifying fault-tolerant, real-time programs. Such a program needs to be provably correct according to both its functional and real-time requirements, despite the possible occurrence of system failures. The paper demonstrates that a suitably expressive logic for real-time systems makes it possible to naturally model the state changes caused by system failures and determine their effect on the functional and real-time properties of executions.
16579361
A Theory of Reactive Components
We present a theory of reactive components. We identify a component by its provided services, and specify the individual services by a guarded-design, which enables one to separate the responsibility of clients from the commitment made by the component, and model the behaviour of a component by a set of failures and divergences. Protocols are introduced to coordinate the interactions between a component and its environment. We adopt the notion of process refinement to formalise the substitutivity of components, and provide a complete proof method based on the notion of simulations. We also study the algebraic properties of component combinators.
11468499
Secure Information Flow in Mobile Bootstrapping Process
The security of bootstrapping is very important for mobile computing. In this paper, we present the bootstrapping process of the Cherubim security system which uses a smartcard to allow a mobile Cherubim client to universally access remote standard services. In order to prevent any leakage of sensitive information, we apply a type system for secure flows to the bootstrapping source codes. The type system guarantees that well-typed programs satisfy a noninterference security property. This means that the program does not ``leak'''' sensitive data. The type system also produces principal types for type-correct programs that characterize how programs can be called securely. The analysis demonstrates that the type system can ensure secure flow enforcement.
11533242
Multi-robot mobility enhanced hop-count based localization in ad hoc networks
The localization problem is important in mobile robots and wireless sensor network and has been studied for many years. Among many localization methods, the hop-count based approach is simple and scalable; however, the localization accuracy is not satisfactory if the node density is low. To solve this problem, in this paper a multi-robot approach is proposed to utilize the cooperation and mobility of the robots to improve the node distribution (density), thus enhancing the hop-count based localization. By an auction-based task allocation scheme, the robots can negotiate with the static sensor nodes and then select the most suitable robots to move to the area of sparse node density, thus increasing the localization accuracy for the static sensor nodes. On the other hand, the robots also can localize themselves with the help of the static sensor nodes. The efficacy of this approach is shown by simulation.
15724338
Stochastic Scheduling with Variable Profile and Precedence Constraints
In this paper, we consider the stochastic profile scheduling problem of a partially ordered set of tasks on uniform processors. The set of available processors varies in time. The running times of the tasks are independent random variables with exponential distributions. We obtain a sufficient condition under which a list policy stochastically minimizes the makespan within the class of preemptive policies. This result allows us to obtain a simple optimal policy when the partial order is an interval order, an in-forest, or an out-forest.