Luis F. Marin-Urias

Conception and Implementation of a Supermarket Shopping Assistant System

In this paper we present the design framework of a shopping assistant system to be used in supermarkets mainly by elderly or disabled people. The whole system is based on the interaction of three different kinds of electronic devices: a) mobile devices that users carry with them (smart phones or electronic tablets), b) autonomous mobile robots assisting users by displaying information and carrying groceries, and finally, c) the supermarket technological infrastructure (database servers, Wi-Fi and Bluetooth access points, etc.). These components interact through a common technological platform, allowing the user to prepare his/her shopping list, and then using it with the robot as an assistant, during his/her shopping process.

Design, integration, and test of a shopping assistance robot system

In this paper is described the current work towards the design of a shopping assistant robot system. This system will allow users to keep control of what they are buying; the robot will help the customer by handling its shopping list, carrying with all the products, and serving as a companion. In this work is also shown the acceptability studies for this kind of robot.

Using color histograms and range data to track trajectories of moving people from a mobile robot platform

People detection and tracking is still an active research field for autonomous mobile robots. Approaches that tackle the problem on mobile robots differ from those proposed for surveillance and other similar tasks. Mainly due to the motion of sensors and hence the complexity of scene interpretation, approaches proposed for fixed cameras are not appropriate. In this paper it is presented a methodology for people detection and tracking from an autonomous mobile robot. People detection and tracking initialization is made by image processing techniques, while for tracking data provided a range data camera (Kinect like sensor) and color information from the former sensor are used to track people over 3D space. Accuracy of tracker is achieved by an adaptive color histograms method based on color from RGB camera and projected over the plain view.

Floor plane recovery from monocular vision for autonomous mobile robot on indoor environments

Floor plane recovery is a very important issue on mobile robotics. Without the using of specialized hardware as Laser Range Finders (LRF) or some others optical time-of-flight sensors, plane recovery is really a challenge. In this paper we present a robust approach for plane recovery from monocular images coming from an uncalibrated active Pan/Tilt/Zoom (PTZ) camera mounted on a mobile robot platform. Floor plane is obtained by tracking features, as interest points, between two sequential images taken by the robot camera. Projective invariants are measured over groups of five non-three collinear feature points, in order to detect groups of points on the same plane. Then homographies are calculated for each invariant group of points and finally by a vote system the homography with a higher value, determines the major plane on the image sequence.

A memory game for human-robot interaction

As a part of the final goal of introducing robots in the human environment, it also comes the problem of the close interaction between these two beings. Close cooperative activities illustrate well this problem and rises new challenges to solve. In this report we show the current work of the development of a system for acquiring information directly from human focused on a classic interaction game called “Simon Says”.