Modelling and reducing uncertainty are two essential problems with mobile robot localisation. In this paper, a new robot position estimator, the Gaussian mixture of Bayes (GMB) which utilises a density estimation technique, is introduced in particular. The proposed system, namely the GMB robot position estimator, which allows a robot's position to be modelled as a probability distribution, and ...

Many conventional methods for multisensor fusion have been based on the prede ned selection such as \which sensor is used for which situation," and mainly they have seemed to concentrated on the reconstruction of a 3-D geometric model of the environment supposing such a model would be generally useful. However, optimality of a priori selection by the programmer is not guaranteed, nor is such a ...

In many multi-robot applications such as target search, environmental monitoring and reconnaissance, the multi-robot system operates semi-autonomously, but under the supervision of a remote human who monitors task progress. In these applications, each robot collects a large amount of task-specific data that must be sent to the human periodically to keep the human aware of task progress. It is o...

This paper introduces a novel neural network-based reinforcement learning approach for robot gaze control. Our approach enables a robot to learn and adapt its gaze control strategy for human-robot interaction without the use of external sensors or human supervision. The robot learns to focus its attention on groups of people from its own audio-visual experiences, and independently of the number...

Self-sustenance in an unknown environment for an autonomous mobile robot with restricted sensory faculties is a challenging problem, primarily due to lack of effectiveness of existing techniques (deterministic or learning-based) in real world. Through this thesis, we try to investigate the utility of some of the existing reinforcement learning based techniques in achieving energy self-sufficien...

due to their advantages, omni-directional mobile robots have found many applications especially in robotic soccer competitions. however, omni directional navigation system, omni-vision system and kicking mechanism in such mobile robots have not ever been combined. this situation brings the idea of a robot with no head direction into existence, a comprehensive omni directional mobile robot. such...

This paper presents an original application of the Galois lattice theory, the visual landmark selection for topological localization of an autonomous mobile robot, equipped with a color camera. First, visual landmarks have to be selected in order to characterize a structural environment. Second, such landmarks have to be detected and updated for localization. These landmarks are combinations of...

This paper addresses the problem of a features selection criterion for a simultaneous localization and mapping (SLAM) algorithm implemented on a mobile robot. This SLAM algorithm is a sequential extended Kalman filter (EKF) implementation that extracts corners and lines from the environment. The selection procedure is made according to the convergence theorem of the EKF-based SLAM. Thus, only t...

A major challenge to the deployment of mobile robots in a wide range of tasks is the ability to function autonomously, learning appropriate models for environmental features and adapting these models in response to environmental changes. Such autonomous operation is feasible iff the robot is able to plan an appropriate action sequence. In this paper, we focus on the task of color modeling/learn...