Quantitative analysis of accuracy of an inertial/acoustic 6DOF tracking system in motion

An increasing number of neuroscience experiments are using virtual reality to provide a more immersive and less artificial experimental environment. This is particularly useful to navigation and three-dimensional scene perception experiments. Such experiments require accurate real-time tracking of the observer's head in order to render the virtual scene. Here, we present data on the accuracy of a commonly used six degrees of freedom tracker (Intersense IS900) when it is moved in ways typical of virtual reality applications. We compared the reported location of the tracker with its location computed by an optical tracking method. When the tracker was stationary, the root mean square error in spatial accuracy was 0.64 mm. However, we found that errors increased over ten-fold (up to 17 mm) when the tracker moved at speeds common in virtual reality applications. We demonstrate that the errors we report here are predominantly due to inaccuracies of the IS900 system rather than the optical tracking against which it was compared. (c) 2006 Elsevier B.V. All rights reserved.

Results of applying sensor fusion to a control system using optic flow

The results from applying a sensor fusion process to an adaptive controller used to balance all inverted pendulum axe presented. The goal of the sensor fusion process was to replace some of the four mechanical measurements, which are known to be sufficient inputs for a linear state feedback controller to balance the system, with optic flow variables. Results from research into the psychology of the sense of balance in humans were the motivation for the investigation of this new type of controller input. The simulated model of the inverted pendulum and the virtual reality environments used to provide the optical input are described. The successful introduction of optical information is found to require the preservation of at least two of the traditional input types and entail increased training till-le for the adaptive controller and reduced performance (measured as the time the pendulum remains upright)

Investigating the feasibility of a swarm-array computing approach

The work reported in this paper proposes a novel synergy between parallel computing and swarm robotics to offer a new computing paradigm, 'swarm-array computing' that can harness and apply autonomic computing for parallel computing systems. One approach among three proposed approaches in swarm-array computing based on landscapes of intelligent cores, in which the cores of a parallel computing system are abstracted to swarm agents, is investigated. A task is executed and transferred seamlessly between cores in the proposed approach thereby achieving self-ware properties that characterize autonomic computing. FPGAs are considered as an experimental platform taking into account its application in space robotics. The feasibility of the proposed approach is validated on the SeSAm multi-agent simulator.

An autonomic approach in swarm-array computing

Can autonomic computing concepts be applied to traditional multi-core systems found in high performance computing environments? In this paper, we propose a novel synergy between parallel computing and swarm robotics to offer a new computing paradigm, `Swarm-Array Computing' that can harness and apply autonomic computing for parallel computing systems. One approach among three proposed approaches in swarm-array computing based on landscapes of intelligent cores, in which the cores of a parallel computing system are abstracted to swarm agents, is investigated. A task gets executed and transferred seamlessly between cores in the proposed approach thereby achieving self-ware properties that characterize autonomic computing. FPGAs are considered as an experimental platform taking into account its application in space robotics. The feasibility of the proposed approach is validated on the SeSAm multi-agent simulator.

Towards self-ware via swarm-array computing

The work reported in this paper proposes Swarm-Array computing, a novel technique inspired by swarm robotics, and built on the foundations of autonomic and parallel computing. The approach aims to apply autonomic computing constructs to parallel computing systems and in effect achieve the self-ware objectives that describe self-managing systems. The constitution of swarm-array computing comprising four constituents, namely the computing system, the problem/task, the swarm and the landscape is considered. Approaches that bind these constituents together are proposed. Space applications employing FPGAs are identified as a potential area for applying swarm-array computing for building reliable systems. The feasibility of a proposed approach is validated on the SeSAm multi-agent simulator and landscapes are generated using the MATLAB toolkit.

Intermittently-visual tracking experiments reveal the roles of error-correction and predictive mechanisms in the human visual-motor control system

Prediction mechanism is necessary for human visual motion to compensate a delay of sensory-motor system. In a previous study, “proactive control” was discussed as one example of predictive function of human beings, in which motion of hands preceded the virtual moving target in visual tracking experiments. To study the roles of the positional-error correction mechanism and the prediction mechanism, we carried out an intermittently-visual tracking experiment where a circular orbit is segmented into the target-visible regions and the target-invisible regions. Main results found in this research were following. A rhythmic component appeared in the tracer velocity when the target velocity was relatively high. The period of the rhythm in the brain obtained from environmental stimuli is shortened more than 10%. The shortening of the period of rhythm in the brain accelerates the hand motion as soon as the visual information is cut-off, and causes the precedence of hand motion to the target motion. Although the precedence of the hand in the blind region is reset by the environmental information when the target enters the visible region, the hand motion precedes the target in average when the predictive mechanism dominates the error-corrective mechanism.

The SAFEE on-board threat detection system

Under the framework of the European Union Funded SAFEE project(1), this paper gives an overview of a novel monitoring and scene analysis system developed for use onboard aircraft in spatially constrained environments. The techniques discussed herein aim to warn on-board crew about pre-determined indicators of threat intent (such as running or shouting in the cabin), as elicited from industry and security experts. The subject matter experts believe that activities such as these are strong indicators of the beginnings of undesirable chains of events or scenarios, which should not be allowed to develop aboard aircraft. This project aimes to detect these scenarios and provide advice to the crew. These events may involve unruly passengers or be indicative of the precursors to terrorist threats. With a state of the art tracking system using homography intersections of motion images, and probability based Petri nets for scene understanding, the SAFEE behavioural analysis system automatically assesses the output from multiple intelligent sensors, and creates. recommendations that are presented to the crew using an integrated airborn user interface. Evaluation of the system is conducted within a full size aircraft mockup, and experimental results are presented, showing that the SAFEE system is well suited to monitoring people in confined environments, and that meaningful and instructive output regarding human actions can be derived from the sensor network within the cabin.

Landscape of intelligent cores: An autonomic multi-agent approach for space application

Space applications are challenged by the reliability of parallel computing systems (FPGAs) employed in space crafts due to Single-Event Upsets. The work reported in this paper aims to achieve self-managing systems which are reliable for space applications by applying autonomic computing constructs to parallel computing systems. A novel technique, 'Swarm-Array Computing' inspired by swarm robotics, and built on the foundations of autonomic and parallel computing is proposed as a path to achieve autonomy. The constitution of swarm-array computing comprising for constituents, namely the computing system, the problem / task, the swarm and the landscape is considered. Three approaches that bind these constituents together are proposed. The feasibility of one among the three proposed approaches is validated on the SeSAm multi-agent simulator and landscapes representing the computing space and problem are generated using the MATLAB.

Intelligent agents: are they feasible in swarm-array computing?

The work reported in this paper proposes 'Intelligent Agents', a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent approach, a task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and can be seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-* objectives of autonomic computing. The approach is validated on a multi-agent simulator.

Intelligent cores and intelligent agents: two approaches to achieve autonomy in swarm-array computing

How can a bridge be built between autonomic computing approaches and parallel computing systems? How can autonomic computing approaches be extended towards building reliable systems? How can existing technologies be merged to provide a solution for self-managing systems? The work reported in this paper aims to answer these questions by proposing Swarm-Array Computing, a novel technique inspired from swarm robotics and built on the foundations of autonomic and parallel computing paradigms. Two approaches based on intelligent cores and intelligent agents are proposed to achieve autonomy in parallel computing systems. The feasibility of the proposed approaches is validated on a multi-agent simulator.

An assessment of eye-gaze potential within immersive virtual environments

In collaborative situations, eye gaze is a critical element of behavior which supports and fulfills many activities and roles. In current computer-supported collaboration systems, eye gaze is poorly supported. Even in a state-of-the-art video conferencing system such as the access grid, although one can see the face of the user, much of the communicative power of eye gaze is lost. This article gives an overview of some preliminary work that looks towards integrating eye gaze into an immersive collaborative virtual environment and assessing the impact that this would have on interaction between the users of such a system. Three experiments were conducted to assess the efficacy of eye gaze within immersive virtual environments. In each experiment, subjects observed on a large screen the eye-gaze behavior of an avatar. The eye-gaze behavior of that avatar had previously been recorded from a user with the use of a head-mounted eye tracker. The first experiment was conducted to assess the difference between users' abilities to judge what objects an avatar is looking at with only head gaze being viewed and also with eye- and head-gaze data being displayed. The results from the experiment show that eye gaze is of vital importance to the subjects, correctly identifying what a person is looking at in an immersive virtual environment. The second experiment examined whether a monocular or binocular eye-tracker would be required. This was examined by testing subjects' ability to identify where an avatar was looking from their eye direction alone, or by eye direction combined with convergence. This experiment showed that convergence had a significant impact on the subjects' ability to identify where the avatar was looking. The final experiment looked at the effects of stereo and mono-viewing of the scene, with the subjects being asked to identify where the avatar was looking. This experiment showed that there was no difference in the subjects' ability to detect where the avatar was gazing. This is followed by a description of how the eye-tracking system has been integrated into an immersive collaborative virtual environment and some preliminary results from the use of such a system.

Achieving intelligent agents and its feasibility in swarm-array computing

The work reported in this paper proposes ‘Intelligent Agents’, a Swarm-Array computing approach focused to apply autonomic computing concepts to parallel computing systems and build reliable systems for space applications. Swarm-array computing is a robotics a swarm robotics inspired novel computing approach considered as a path to achieve autonomy in parallel computing systems. In the intelligent agent approach, a task to be executed on parallel computing cores is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and can be seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-* objectives of autonomic computing. The approach is validated on a multi-agent simulator.

An Integrated Traffic and Pedestrian Model_based Vision System

The paper describes a novel integrated vision system in which two autonomous visual modules are combined to interpret a dynamic scene. The first module employs a 3D model-based scheme to track rigid objects such as vehicles. The second module uses a 2D deformable model to track non-rigid objects such as people. The principal contribution is a novel method for handling occlusion between objects within the context of this hybrid tracking system. The practical aim of the work is to derive a scene description that is sufficiently rich to be used in a range of surveillance tasks. The paper describes each of the modules in outline before detailing the method of integration and the handling of occlusion in particular. Experimental results are presented to illustrate the performance of the system in a dynamic outdoor scene involving cars and people.

3D path planning with novel multiple 2D layered approach for complex human-robot interaction

Navigating cluttered indoor environments is a difficult problem in indoor service robotics. The Acroboter concept, a novel approach to indoor locomotion, represents unique opportunity to avoid obstacles in indoor environments by navigating the ceiling plane. This mode of locomotion requires the ability to accurately detect obstacles, and plan 3D trajectories through the environment. This paper presents the development of a resilient object tracking system, as well as a novel approach to generating 3D paths suitable for such robot configurations. Distributed human-machine interfacing allowing simulation previewing of actions is also considered in the developed system architecture.