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Computers will soon be powerful enough to simulate consciousness. The artificial life community should start to try to understand how consciousness could be simulated. The proposal is to build an artificial life system in which consciousness might be able to evolve. The idea is to develop internet-wide artificial universe in which the agents can evolve. Users play games by defining agents that form communities. The communities have to perform tasks, or compete, or whatever the specific game demands. The demands should be such that agents that are more aware of their universe are more likely to succeed. The agents reproduce and evolve within their user’s machine, but can also sometimes transfer to other machine across the internet. Users will be able to choose the capabilities of their agents from a fixed list, but may also write their own powers for their agents.
We developed a scene text recognition system with active vision capabilities, namely: auto-focus, adaptive aperture control and auto-zoom. Our localization system is able to delimit text regions in images with complex backgrounds, and is based on an attentional cascade, asymmetric adaboost, decision trees and Gaussian mixture models. We think that text could become a valuable source of semantic information for robots, and we aim to raise interest in it within the robotics community. Moreover, thanks to the robot’s pan-tilt-zoom camera and to the active vision behaviors, the robot can use its affordances to overcome hindrances to the performance of the perceptual task. Detrimental conditions, such as poor illumination, blur, low resolution, etc. are very hard to deal with once an image has been captured and can often be prevented. We evaluated the localization algorithm on a public dataset and one of our own with encouraging results. Furthermore, we offer an interesting experiment in active vision, which makes us consider that active sensing in general should be considered early on when addressing complex perceptual problems in embodied agents.
This paper presents recent research on an active multispectral scanning sensor capable of classifying an object's surface material in order to distinguish between different kinds of materials and human skin. The sensor itself has already been presented in previous work and can be used in conjunction with safeguarding equipment at manually-fed machines or robot workplaces, for example. This work shows how an extended sensor system with advanced material classifiers can be used to provide additional value by distinguishing different materials of work pieces in order to suggest different tools or parameters for the machine (e.g. the use of a different saw blade or rotation speed at table saws). Additionally, a first implementation and evaluation of an active multispectral camera system addressing new safety applications is described. Both approaches intend to increase the productivity and the user's acceptance of the sensor technology.
Application performance improvements through VM parameter modification after runtime analysis
(2013)
Switched power electronic subsystems are widely used in various applications. A fault in one of their components may have a significant effect on the system’s load or may even cause a damage. Therefore, it is important to detect and isolate faults and to report true faults to a supervisory system in order to avoid malfunction of or damage to a load. If, in a model-based approach to fault detection and isolation of hybrid systems, switching devices are considered as ideal switches then some equations must be reformulated whenever some devices have switched. In this paper, a fixed causality bond graph representation of hybrid system models is used, i.e., computational causalities assigned according to the Standard Causality Assignment Procedure (SCAP) are independent of system modes of operation. The latter are taken into account by transformer moduli mi(t) ∈ {0, 1} ∀t ≥ 0 in a unique set of equations of motion. In a case study, this approach is used for fault diagnosis in a three-phase full-wave rectifier. Residuals of Analytical Redundancy Relations (ARRs) holding for all modes of operations and serving as fault indicators are computed in an offline simulation as part of a DAE system by using a bond graph model of the faulty system instead of the real one and by coupling it to a bond graph of the healthy system by means of residual sinks.
Die Vorstandsperspektive
(2013)
Realism and plausibility of computer controlled entities in entertainment software have been enhanced by adding both static personalities and dynamic emotions. Here a generic model is introduced which allows the transfer of findings from real-life personality studies to a computational model. This information is used for decision making. The introduction of dynamic event-based emotions enables adaptive behavior patterns. The advantages of this new model have been validated with a four-way crossroad in a traffic simulation. Driving agents using the introduced model enhanced by dynamics were compared to agents based on static personality profiles and simple rule-based behavior. It has been shown that adding an adaptive dynamic factor to agents improves perceivable plausibility and realism. It also supports coping with extreme situations in a fair and understandable way.
Generating and visualizing large areas of vegetation that look natural makes terrain surfaces much more realistic. However, this is a challenging field in computer graphics, because ecological systems are complex and visually appealing plant models are geometrically detailed. This work presents Silva (System for the Instantiation of Large Vegetated Areas), a system to generate and visualize large vegetated areas based on the ecological surrounding. Silva generates vegetation on Wang-tiles with associated reusable distributions enabling multi-level instantiation. This paper presents a method to generate Poisson Disc Distributions (PDDs) with variable radii on Wang-tile sets (without a global optimization) that is able to generate seamless tilings. Because Silva has a freely configurable generation pipeline and can consider plant neighborhoods it is able to incorporate arbitrary abiotic and biotic components during generation. Based on multi-levelinstancing and nested kd-trees, the distributions on the Wang-tiles allow their acceleration structures to be reused during visualization. This enables Silva to visualize large vegetated areas of several hundred square kilometers with low render times and a small memory footprint.
Grailog embodies a systematics to visualize knowledge sources by graphical elements. Its main benefit is that the resulting visual presentations are easier to read for humans than the original symbolic source code. In this paper we introduce a methodology to handle the mapping from Datalog RuleML, serialized in XML, to an SVG representation of Grailog, also serialized in XML, via eXtensible Stylesheet Language Transformations (XSLT) 2.0/XML; the SVG is then rendered visually by modern Web browsers. This initial mapping is realized to target Grailog's "fully node copied" normal form. Elements can thus be translated one at a time, separating the fundamental Datalog-to-SVG translation concern from the concern of merging node copies for optimal (hyper)graph layout and avoiding its high computational complexity in this online tool. The resulting open source Grailog Knowledge-Source Visualizer (Grailog KS Viz) supports Datalog RuleML with positional relations of arity n>1. The on-the-fly transformation was shown to run on all recent major Web browsers and should be easy to understand, use, and extend.
Improving Robustness of Task Execution Against External Faults Using Simulation Based Approach
(2013)
Robots interacting in complex and cluttered environments may face unexpected situations referred to as external faults which prohibit the successful completion of their tasks. In order to function in a more robust manner, robots need to recognise these faults and learn how to deal with them in the future. We present a simulation-based technique to avoid external faults occurring during execusion releasing actions of a robot. Our technique utilizes simulation to generate a set of labeled examples which are used by a histogram algorithm to compute a safe region. A safe region consists of a set of releasing states of an object that correspond to successful performances of the action. This technique also suggests a general solution to avoid the occurrence of external faults for not only the current, observable object but also for any other object of the same shape but different size.
Embodied artificial agents operating in dynamic, real-world environments need architectures that support the special requirements that exist for them. Architectures are not always designed from scratch and the system then implemented all at once, but rather, a step-wise integration of components is often made to increase functionality. Our work aims to increase flexibility and robustness by integrating a task planner into an existing architecture and coupling the planning process with the preexisting execution and the basic monitoring processes. This involved the conversion of monolithic SMACH scenario scripts (state-machine execution scripts) into modular states that can be called dynamically based on the plan that was generated by the planning process. The procedural knowledge encoded in such state machines was used to model the planning domain for two RoboCup@Home scenarios on a Care-O-Bot 3 robot [GRH+08]. This was done for the JSHOP2 [IN03] hierarchical task network (HTN) planner. A component which iterates through a generated plan and calls the appropriate SMACH states [Fie11] was implemented, thus enabling the scenarios. Crucially, individual monitoring actions which enable the robot to monitor the execution of the actions were designed and included, thus providing additional robustness.