Drazen Brscic

Human-Observation-Based Extraction of Path Patterns for Mobile Robot Navigation

In this paper, a mobile robot navigation method based on the observation of human walking is presented. The proposed method extracts paths that are frequently used by human and builds a topological map of the environment from the observed human walking paths. Unlike the conventional methods, the proposed method enables us to generate paths which are practical, have no obstacles, and are natural for humans since the paths reflect the motion of persons. For realizing the human observation in a large area, in this paper, multiple vision sensors are placed in space. By using distributed sensors, people can be observed even when the robot is not near them or if they are hidden behind obstacles. Mobile robot navigation based on the topological map is also performed with the support of the distributed sensors. The global position of the mobile robot can be directly measured by using external sensors, which makes the localization problem much easier. Based on the position information, the mobile robot can follow the generated paths and reach the goal point while avoiding obstacles.

Tracking of Objects in Intelligent Space Using Laser Range Finders

In this paper we present an approach to tracking of humans and mobile robots in spaces with ubiquitous distributed sensors and actuators - Intelligent Spaces. In order to be able to implement services that depend on the position of humans, a reliable tracking method is needed. Also, for the implementation of mobile robot control it is important to know both the robots and humans positions. In this work we present an implementation based on laser range finders. First, a short survey of the existing tracking methods, and their applicability to tracking of objects in intelligent environments is presented. Based on those results, we chose laser range finders for measurement. The method we use is based on clustering of the foreground of the measurement and tracking the position using a Kalman filter. Experimental results of tracking mobile robots and humans are given which confirm the applicability of the presented method.

Implementation of Mobile Robot Control in Intelligent Space

In this paper we present the implementation of mobile robot control in the intelligent space (iSpace). The mobile robot in iSpace is primarily used as a mean of offering physical services to users, or as a mobile sensor for providing more details about the space. On the other hand, the distributed sensors in iSpace offer advantages in standard robot control tasks. In this paper the details of the engagement of mobile robots in iSpace are given. Moreover, the details of the implementation of the mobile robot localization mapping and navigation are described in detail and experimental results are given

Tracking of Humans Inside Intelligent Space using Static and Mobile Sensors

In this paper we present an approach to tracking of humans in spaces with ubiquitous distributed sensors and actuators - Intelligent Spaces. In order to be able to implement services that depend on the position of humans, a reliable tracking method is needed. In addition to the sensors distributed in space, mobile sensors are also considered. A mobile sensor is a mobile robot equipped with onboard sensors, which can be used to improve the estimate. Here we present an implementation based on laser range finders and track the position of humans, as well as the mobile robot, using a Kalman filter. Characteristics of such a tracking system are analyzed and experimental results are shown.

Comparison of robot localization methods using distributed and onboard laser range finders

In this paper we discuss methods for estimating the position of objects in environments that have both distributed sensing devices as well as mobile robots equipped with sensors - intelligent spaces. The aim is to use both types of devices for the estimation. We focus on the utilization of laser range finder devices as sensors, due to their good sensing characteristics. Our main interest here is in the localization of mobile robots and we consider two estimation methods. One is based on a heuristic determination of the center of the tracked object and utilizes a Kalman filter based estimation approach. The other method is based on geometric models of both the environment and the robot, and the position is estimated using a particle filter. The methods are described and experimental results are shown, and their comparison is given.

Model based robot localization using onboard and distributed laser range finders

In this paper we present a method for estimating the position of mobile robots using a combination of both robotpsilas onboard sensors and sensors at fixed locations in the environment, where we use laser range finders as sensors. This is a situation which arises in so-called intelligent spaces, where there are both static sensors and mobile robots present. The method we present extends the robot localization methods based on occupancy grids, however here occupancy grids are used to represent not only the geometry of the environment but also that of the robot. For tracking the robot we employ a particle filter. The details of the method are given and experimental results are shown to illustrate the method.

3D visualization for Intelligent Space: Time-delay compensation in a remote controlled environment

By virtually re-creating and visualizing an intelligent space (iSpace) geographically far from the original version, one opens up the possibility of remote control and interaction between the real iSpace and the virtual copy. Here we present the required components for such a mixed environment: the actual iSpace in a form of a laboratory built for such experiments, the stereoscopic (real 3D) visualization tool at the far end to reproduce the original iSpace, and the middleware embodied by the computer network that connects the two. To remotely operate in the iSpace one has to overcome the important problem of synchronization that is made difficult by the time delay in the computer network. Here we present our first approach to solve this problem by demonstrating a successful remote control of a mobile robot in this mixed environment.

Implementation of Distributed Sensor Network for Intelligent Space

In this paper, we introduce a basic framework of intelligent space (iSpace) and automated calibration of the distributed sensors using mobile robots. iSpace is a room or area where many intelligent sensors and actuators are distributed and networked. In iSpace, the embedded sensors can monitor the whole environment by communicating with each other through the network. Based on the observed information, the actuators provide informative and physical services to users. In order to implement such a system, a basic framework which realizes a close cooperation among distributed devices has to be considered. We propose a layered structure which consists of four layers -the sensor node layer, the basic information sever layer, the application layer and the actuator layer. The structure makes it possible to fuse information extracted by each sensor node effectively and provides flexibility and scalability to the system. Moreover, one of the major problems when setting up the devices is calibration of the sensors. In order to solve this, we utilize mobile robots in iSpace. The mobility of mobile robots allows us to cover wide areas of the environment without placing many landmarks in exactly known positions beforehand. Automated calibration of distributed laser range finders is performed based on the positions of the mobile robot in world coordinate system and their corresponding points in local coordinate system.

Acting in intelligent space - mobile robot control based on sensors distributed in space -

This paper presents our implementation of the control of mobile robot as actuator in intelligent space. The intelligent space has distributed sensors that can be used for tracking and mapping the space. Furthermore, it can use these measurements to control a mobile robot in the space. This way physical acting inside the space can be achieved. Here we present our developed intelligent space system that uses laser range finders for and a mobile robot as actuator. Methods and obtained results are described.