Neural network control of a simple mobile robot

In recent years researchers in the Department of Cybernetics have been developing simple mobile robots capable of exploring their environment on the basis of the information obtained from a few simple sensors. These robots are used as the test bed for exploring various behaviours of single and multiple organisms: the work is inspired by considerations of natural systems. In this paper we concentrate on that part of the work which involves neural networks and related techniques. These neural networks are used both to process the sensor information and to develop the strategy used to control the robot. Here the robots, their sensors, and the neural networks used and all described. 1.

Motion estimation through approximated densities

Many techniques are currently used for motion estimation. In the block-based approaches the most common procedure applied is the block-matching based on various algorithms. To refine the motion estimates resulting from the full search or any coarse search algorithm, one can find few applications of Kalman filtering, mainly in the intraframe scheme. The Kalman filtering technique applicability for block-based motion estimation is rather limited due to discontinuities in the dynamic behaviour of the motion vectors. Therefore, we propose an application of the concept of the filtering by approximated densities (FAD). The FAD, originally introduced to alleviate limitations due to conventional Kalman modelling, is applied to interframe block-motion estimation. This application uses a simple form of FAD involving statistical characteristics of multi-modal distributions up to second order.

Performance statistics of a head-operated force-reflecting rehabilitation robot system

Researchers in the rehabilitation engineering community have been designing and developing a variety of passive/active devices to help persons with limited upper extremity function to perform essential daily manipulations. Devices range from low-end tools such as head/mouth sticks to sophisticated robots using vision and speech input. While almost all of the high-end equipment developed to date relies on visual feedback alone to guide the user providing no tactile or proprioceptive cues, the “low-tech” head/mouth sticks deliver better “feel” because of the inherent force feedback through physical contact with the user's body. However, the disadvantage of a conventional head/mouth stick is that it can only function in a limited workspace and the performance is limited by the user's strength. It therefore seems reasonable to attempt to develop a system that exploits the advantages of the two approaches: the power and flexibility of robotic systems with the sensory feedback of a headstick. The system presented in this paper reflects the design philosophy stated above. This system contains a pair of master-slave robots with the master being operated by the user's head and the slave acting as a telestick. Described in this paper are the design, control strategies, implementation and performance evaluation of the head-controlled force-reflecting telestick system.

Investigating a robot as a therapy partner for children with autism

The aurora project is investigating the possibility of using a robotic platform as a therapy aid for--children with autism. Because of the nature of this disability, the robot could be beneficial in its ability--to present the children with a safe and comfortable environment and allow them to explore and learn--about the interaction space involved in social situations. The robotic platform is able to present--information along a limited number of channels and in a manner which the children are familiar with--from television and cartoons. Also, the robot is potentially able to adapt its behaviour and to allow the--children to develop at their own rates. Initial trial results are presented and discussed, along with the--rationale behind the project and its goals and motivations. The trial procedure and methodology are--explained and future work is highlighted.

Evaluating the response of children with autism to a robot

Since 1998, the Aurora project has been investigating the use of a robotic platform as a tool for therapy use with children with autism. A key issue in this project is the evaluation of the interactions, which are not constricted and involve the child moving freely. Additionally, the response of the children is an important factor which must emerge from the robot trial sessions and the evaluation methodology, in order to guide further development work.

Minimum jerk trajectory control for rehabilitation and haptic applications

Smooth trajectories are essential for safe interaction in between human and a haptic interface. Different methods and strategies have been introduced to create such smooth trajectories. This paper studies the creation of human-like movements in haptic interfaces, based on the study of human arm motion. These motions are intended to retrain the upper limb movements of patients that lose manipulation functions following stroke. We present a model that uses higher degree polynomials to define a trajectory and control the robot arm to achieve minimum jerk movements. It also studies different methods that can be driven from polynomials to create more realistic human-like movements for therapeutic purposes.

Driving saccade to pursuit using image motion

Within the context of active vision, scant attention has been paid to the execution of motion saccades—rapid re-adjustments of the direction of gaze to attend to moving objects. In this paper we first develop a methodology for, and give real-time demonstrations of, the use of motion detection and segmentation processes to initiate capture saccades towards a moving object. The saccade is driven by both position and velocity of the moving target under the assumption of constant target velocity, using prediction to overcome the delay introduced by visual processing. We next demonstrate the use of a first order approximation to the segmented motion field to compute bounds on the time-to-contact in the presence of looming motion. If the bound falls below a safe limit, a panic saccade is fired, moving the camera away from the approaching object. We then describe the use of image motion to realize smooth pursuit, tracking using velocity information alone, where the camera is moved so as to null a single constant image motion fitted within a central image region. Finally, we glue together capture saccades with smooth pursuit, thus effecting changes in both what is being attended to and how it is being attended to. To couple the different visual activities of waiting, saccading, pursuing and panicking, we use a finite state machine which provides inherent robustness outside of visual processing and provides a means of making repeated exploration. We demonstrate in repeated trials that the transition from saccadic motion to tracking is more likely to succeed using position and velocity control, than when using position alone.

Robot free will

We introduce the perspex machine which unifies projective geometry and Turing computation and results in a supra-Turing machine. We show two ways in which the perspex machine unifies symbolic and non-symbolic AI. Firstly, we describe concrete geometrical models that map perspexes onto neural networks, some of which perform only symbolic operations. Secondly, we describe an abstract continuum of perspex logics that includes both symbolic logics and a new class of continuous logics. We argue that an axiom in symbolic logic can be the conclusion of a perspex theorem. That is, the atoms of symbolic logic can be the conclusions of sub-atomic theorems. We argue that perspex space can be mapped onto the spacetime of the universe we inhabit. This allows us to discuss how a robot might be conscious, feel, and have free will in a deterministic, or semi-deterministic, universe. We ground the reality of our universe in existence. On a theistic point, we argue that preordination and free will are compatible. On a theological point, we argue that it is not heretical for us to give robots free will. Finally, we give a pragmatic warning as to the double-edged risks of creating robots that do, or alternatively do not, have free will.

Complete robot-eye calibration without special calibration objects

A robot mounted camera is useful in many machine vision tasks as it allows control over view direction and position. In this paper we report a technique for calibrating both the robot and the camera using only a single corresponding point. All existing head-eye calibration systems we have encountered rely on using pre-calibrated robots, pre- calibrated cameras, special calibration objects or combinations of these. Our method avoids using large scale non-linear optimizations by recovering the parameters in small dependent groups. This is done by performing a series of planned, but initially uncalibrated robot movements. Many of the kinematic parameters are obtained using only camera views in which the calibration feature is at, or near the image center, thus avoiding errors which could be introduced by lens distortion. The calibration is shown to be both stable and accurate. The robotic system we use consists of camera with pan-tilt capability mounted on a Cartesian robot, providing a total of 5 degrees of freedom.