From saccades to smooth pursuit: real-time gaze control using motion feedback

The authors present an active vision system which performs a surveillance task in everyday dynamic scenes. The system is based around simple, rapid motion processors and a control strategy which uses both position and velocity information. The surveillance task is defined in terms of two separate behavioral subsystems, saccade and smooth pursuit, which are demonstrated individually on the system. It is shown how these and other elementary responses to 2D motion can be built up into behavior sequences, and how judicious close cooperation between vision and control results in smooth transitions between the behaviors. These ideas are demonstrated by an implementation of a saccade to smooth pursuit surveillance system on a high-performance robotic hand/eye platform.

Robots can't really be intelligent can they?

The whole concept of just what is and what is not, intelligence is a vitally important one. As humans interact more with machines, so the similarities and differences between human and machine intelligence need to be looked at in a sensible, scientific way. This paper considers human and machine intelligence and links them closely to physical characteristics, as exhibited by robots. Potential interfaces between humans and machines are also considered, as is the state of the art in direct physical links between humans and machines.

Behaviour and learning in completely autonomous mobile robots

A number of Intelligent Mobile Robots have been developed at the University of Reading. They are completely autonomous in that no umbilical cord attaches to them to extra power supplies or computer station: further, they are not radio controlled. In this paper, the robots are discussed, in their various forms, and the individual behaviours and characteristics which appear are considered.

Path planning of robots in noisy workspaces using learning automata

The problem of a manipulator operating in a noisy workspace and required to move from an initial fixed position P0 to a final position Pf is considered. However, Pf is corrupted by noise, giving rise to Pˆf, which may be obtained by sensors. The use of learning automata is proposed to tackle this problem. An automaton is placed at each joint of the manipulator which moves according to the action chosen by the automaton (forward, backward, stationary) at each instant. The simultaneous reward or penalty of the automata enables avoiding any inverse kinematics computations that would be necessary if the distance of each joint from the final position had to be calculated. Three variable-structure learning algorithms are used, i.e., the discretized linear reward-penalty (DLR-P, the linear reward-penalty (LR-P ) and a nonlinear scheme. Each algorithm is separately tested with two (forward, backward) and three forward, backward, stationary) actions.

Review of computer vision in intelligent environment design

This paper discusses and compares the use of vision based and non-vision based technologies in developing intelligent environments. By reviewing the related projects that use vision based techniques in intelligent environment design, the achieved functions, technical issues and drawbacks of those projects are discussed and summarized, and the potential solutions for future improvement are proposed, which leads to the prospective direction of my PhD research.

Multi-agent collaboration for decision support in shared zones of intelligent buildings

In domain of intelligent buildings, saving energy in buildings and increasing preferences of occupants are two important factors. These factors are the important keys for evaluating the performance of work environment. In recent years, many researchers combine these areas to create the system that can change from original to the modern work environment called intelligent work environment. Due to advance of agent technology, it has received increasing attention in the area of intelligent pervasive environments. In this paper, we review several issues in intelligent buildings, with respect to the implementation of control system for intelligent buildings via multi-agent systems. Furthermore, we present the MASBO (Multi-Agent System for Building cOntrol) that has been implemented for controlling the building facilities to reach the balancing between energy efficiency and occupant’s comfort. In addition to enhance the MASBO system, the collaboration through negotiation among agents is presented.

The indoor localization system using vision for multiple mobile robots

This paper presents the development of an indoor localization system using camera vision. The localization system has a capability to determine 2D coordinate (x, y) for a team of mobile robots, Miabot. The experimental results show that the system outperforms our existing sonar localizer both in accuracy and a precision.

Distributed intelligent management of active networks

This paper focuses on improving computer network management by the adoption of artificial intelligence techniques. A logical inference system has being devised to enable automated isolation, diagnosis, and even repair of network problems, thus enhancing the reliability, performance, and security of networks. We propose a distributed multi-agent architecture for network management, where a logical reasoner acts as an external managing entity capable of directing, coordinating, and stimulating actions in an active management architecture. The active networks technology represents the lower level layer which makes possible the deployment of code which implement teleo-reactive agents, distributed across the whole network. We adopt the Situation Calculus to define a network model and the Reactive Golog language to implement the logical reasoner. An active network management architecture is used by the reasoner to inject and execute operational tasks in the network. The integrated system collects the advantages coming from logical reasoning and network programmability, and provides a powerful system capable of performing high-level management tasks in order to deal with network fault.

Controlling a mobile robot with a biological brain

The intelligent controlling mechanism of a typical mobile robot is usually a computer system. Some recent research is ongoing in which biological neurons are being cultured and trained to act as the brain of an interactive real world robot�thereby either completely replacing, or operating in a cooperative fashion with, a computer system. Studying such hybrid systems can provide distinct insights into the operation of biological neural structures, and therefore, such research has immediate medical implications as well as enormous potential in robotics. The main aim of the research is to assess the computational and learning capacity of dissociated cultured neuronal networks. A hybrid system incorporating closed-loop control of a mobile robot by a dissociated culture of neurons has been created. The system is flexible and allows for closed-loop operation, either with hardware robot or its software simulation. The paper provides an overview of the problem area, gives an idea of the breadth of present ongoing research, establises a new system architecture and, as an example, reports on the results of conducted experiments with real-life robots.