Effects of Transport Delays of Manual Control System Performance

Throughput or transport delays in manual control systems can cause degraded performance and lead to potentially unstable operation. With the expanding use of digital processors, throughput delays can occur in manual control systems in a variety of ways such as in digital flight control systems in real aircraft, and in equation of motion computers and computer generated images in simulators. Research has shown the degrading effect of throughput delays on subjective opinion and system performance and dynamic response. A generic manual control system model is used to provide a relatively simple analysis of and explanation for the effects of various types of delays. The consequence of throughput delays of some simple system architectures is also discussed

The contribution of closed loop tracking control of motion platform on laterally induced postural instability of the drivers at SAAM dynamic simulator

This paper explains the effect of a motion platform closed loop control comparing to the static condition for driving simulators on postural instability. The postural instabilities of the participants (N=18, 15 male and 3 female subjects) were measured as lateral displacements of subject body centre of pressure (YCP ) just before and after each driving session via a balance platform. After having completed the experiments, the two-tailed Mann-Whitney U test was applied to analyze the objective data for merely the post-exposure cases. The objective data analysis revealed that the YCP for the dynamic case indicated a significant lower value than the static situation (U(18), p < 0,0001). It can be concluded that the closed loop tracking control of the hexapod platform of the driving simulator (dynamic platform condition) decreased significantly the lateral postural stability compared to the static operation condition. However the two-tailed Mann-Whitney U test showed that no significant difference was obtained between the two conditions in terms of psychophysical perception

Roll tracking effects of G-vector tilt and various types of motion washout

In a dogfight scenario, the task was to follow the target's roll angle while suppressing gust disturbances. All subjects adopted the same behavioral strategies in following the target while suppressing the gusts, and the MFP-fitted math model response was generally within one data symbol width. The results include the following: (1) comparisons of full roll motion (both with and without the spurious gravity tilt cue) with the static case. These motion cues help suppress disturbances with little net effect on the visual performance. Tilt cues were clearly used by the pilots but gave only small improvement in tracking errors. (2) The optimum washout (in terms of performance close to real world, similar behavioral parameters, significant motion attenuation (60 percent), and acceptable motion fidelity) was the combined attenuation and first-order washout. (3) Various trends in parameters across the motion conditions were apparent, and are discussed with respect to a comprehensive model for predicting adaptation to various roll motion cues

Keyframe-based monocular SLAM: design, survey, and future directions

Extensive research in the field of monocular SLAM for the past fifteen years has yielded workable systems that found their way into various applications in robotics and augmented reality. Although filter-based monocular SLAM systems were common at some time, the more efficient keyframe-based solutions are becoming the de facto methodology for building a monocular SLAM system. The objective of this paper is threefold: first, the paper serves as a guideline for people seeking to design their own monocular SLAM according to specific environmental constraints. Second, it presents a survey that covers the various keyframe-based monocular SLAM systems in the literature, detailing the components of their implementation, and critically assessing the specific strategies made in each proposed solution. Third, the paper provides insight into the direction of future research in this field, to address the major limitations still facing monocular SLAM; namely, in the issues of illumination changes, initialization, highly dynamic motion, poorly textured scenes, repetitive textures, map maintenance, and failure recovery

Predictive Coding for Dynamic Visual Processing: Development of Functional Hierarchy in a Multiple Spatio-Temporal Scales RNN Model

The current paper proposes a novel predictive coding type neural network model, the predictive multiple spatio-temporal scales recurrent neural network (P-MSTRNN). The P-MSTRNN learns to predict visually perceived human whole-body cyclic movement patterns by exploiting multiscale spatio-temporal constraints imposed on network dynamics by using differently sized receptive fields as well as different time constant values for each layer. After learning, the network becomes able to proactively imitate target movement patterns by inferring or recognizing corresponding intentions by means of the regression of prediction error. Results show that the network can develop a functional hierarchy by developing a different type of dynamic structure at each layer. The paper examines how model performance during pattern generation as well as predictive imitation varies depending on the stage of learning. The number of limit cycle attractors corresponding to target movement patterns increases as learning proceeds. And, transient dynamics developing early in the learning process successfully perform pattern generation and predictive imitation tasks. The paper concludes that exploitation of transient dynamics facilitates successful task performance during early learning periods.Comment: Accepted in Neural Computation (MIT press

Suppression of Biodynamic Interference by Adaptive Filtering

Preliminary experimental results obtained in moving base simulator tests are presented. Both for pursuit and compensatory tracking tasks, a strong deterioration in tracking performance due to biodynamic interference is found. The use of adaptive filtering is shown to substantially alleviate these effects, resulting in a markedly improved tracking performance and reduction in task difficulty. The effect of simulator motion and of adaptive filtering on human operator describing functions is investigated. Adaptive filtering is found to substantially increase pilot gain and cross-over frequency, implying a more tight tracking behavior. The adaptive filter is found to be effective in particular for high-gain proportional dynamics, low display forcing function power and for pursuit tracking task configurations

The iso-response method

Throughout the nervous system, neurons integrate high-dimensional input streams and transform them into an output of their own. This integration of incoming signals involves filtering processes and complex non-linear operations. The shapes of these filters and non-linearities determine the computational features of single neurons and their functional roles within larger networks. A detailed characterization of signal integration is thus a central ingredient to understanding information processing in neural circuits. Conventional methods for measuring single-neuron response properties, such as reverse correlation, however, are often limited by the implicit assumption that stimulus integration occurs in a linear fashion. Here, we review a conceptual and experimental alternative that is based on exploring the space of those sensory stimuli that result in the same neural output. As demonstrated by recent results in the auditory and visual system, such iso-response stimuli can be used to identify the non-linearities relevant for stimulus integration, disentangle consecutive neural processing steps, and determine their characteristics with unprecedented precision. Automated closed-loop experiments are crucial for this advance, allowing rapid search strategies for identifying iso-response stimuli during experiments. Prime targets for the method are feed-forward neural signaling chains in sensory systems, but the method has also been successfully applied to feedback systems. Depending on the specific question, “iso-response” may refer to a predefined firing rate, single-spike probability, first-spike latency, or other output measures. Examples from different studies show that substantial progress in understanding neural dynamics and coding can be achieved once rapid online data analysis and stimulus generation, adaptive sampling, and computational modeling are tightly integrated into experiments

Simulation Models for Analyzing the Dynamic Costs of Process-aware Information Systems

Introducing process-aware information systems (PAIS) in enterprises (e.g., workflow management systems, case handling systems) is associated with high costs. Though cost estimation has received considerable attention in software engineering for many years, it is difficult to apply existing approaches to PAIS. This difficulty particularly stems from the inability of existing estimation techniques to deal with the complex interplay of the many technological, organizational and project-driven factors which emerge in the context of PAIS. In response to this problem, this paper proposes an approach which utilizes simulation models for investigating the dynamic costs of PAIS engineering projects. We motivate the need for simulation, discuss the development and execution of simulation models, and give an illustrating example. The present work has been accomplished in the EcoPOST project, which deals with the development of a comprehensive evaluation framework for analyzing PAIS engineering projects from a value-based perspective